Santa Fe Institute Events Wiki - User contributions [en]

CSSS 2010 Santa Fe-Project Presentations

2010-06-23T04:18:42Z

Sergey:

{{CSSS 2010 Santa Fe}}

* [[Evolutionary dynamics of structured genetic algorithms]] - Xin Wang, Felix Hol

* [[Anomalous diffusion on complex networks]] - Lucas Antiqueira, Damian Blasi, Borys Wrobel

* [[Grouping behavior and the evolution of animal migration]] - Andrew Hein, Ana Hocevar, Daniel Jones, Oana Carja, & Kyla Dahlin

* [[Gossip]] - Mark Laidre, Megan Olsen, Daniel Jones, Susanne Shultz, Dan MacKinlay, Katarzyna Samson, Erika Fille Legara, Griffith Rees, Massimiliano Spaziani

* [["Word Bang", The Evolution of Words and Language]] - Nicholas Foti, Julie Granka, Erika Fille Legara, Thomas Maillart, Giovanni Petri

* [[Evolutionary dynamics of fitness-driven walkers on a graph]] - Roberta Sinatra, Erika Fille Legara, Chaitanya Gokhale

* [[What's Happening?]]- [[Lynette Shaw]], [[Sarah Wise]], [[Micael Ehn]], [[Ingrid van Putten]]

* [[Network's shortest paths]]

CSSS 2010 Santa Fe-After Hours

2010-06-17T05:57:38Z

Sergey: /* VLA */

{{CSSS 2010 Santa Fe}}

==Isotopes Game (BASEBALL!!!)==
I am going to the Isotopes baseball game tomorrow (Thursday) night in Albuquerque. The game starts at 7pm, we'll leave at around 6pm. We can stay for as long as we like. I have 4 seats in my car. Who's coming with me? Beer, hotdogs, and baseball, what could be better :-)? ([[Joseph Gran]])

# [[Ana Hocevar]]
# [[Gavin Fay]] As the Kool Aid guy would say, Oh Yea.

== VLA ==
Saturday 19th June - join us on our trip to the [http://www.nrao.edu/index.php/learn/vlavc VLA (Very Large Array)]? ([[Gavin Fay]])

'''[[VLA signup]]'''

I'm interested. I have a car that can hold 3 additional people. [[Anne Johnson]]
* I would also like to go. [[Micael Ehn]]

Ok - talking with Anne and Borys on Friday, I think we decided to aim for next Saturday (the 19th). We'll try and see if we can get a guided tour at such short notice, but plan on going regardless. ([[Gavin Fay]])

* Count me in. [[Ana Hocevar]]
* Am keen to go [[Ingrid van Putten]]
* Interested [[Jonathan Cannon]]
* I'd love to see that thing [[Sergey Melnik]]

==El Rancho de las Golondrinas Field Trip==

Would anyone be interested in a trip to [http://www.golondrinas.org El Rancho de las Golondrinas]? I'd be happy to get one going on Saturday/Sunday.

Sunday most likely. Let me know if y'all are interested. ([[JP]])

I would be interested ([[Bogdan State]])

==SF Complex Art Show==

Opening on Thursday 17th is a 3-night art show at the Santa Fe Complex and other nearby galleries. In the projection dome, they will be showing an installation of Daniel's: [http://www.erase.net/projects/atomswarm/ AtomSwarm], an agent-based sonic ecosystem, which uses swarming behaviours and simulated genetics to create a continually evolving environment.

A few of us are heading down. Anybody interested? Drivers, please make yourself known here!

* I'm going! Probably just Thursday. I believe JP is happy to drive, around 7/7.30ish..? ([[Daniel Jones]])
* I'll try to get there, but I've got lab... [[Jonathan Cannon]]
* I. I shall go, even if i must crawl on my elbows. Although I'd actually prefer a lift. [[User:Dan90|Dan MacKinlay]]

==Soccer==

Lets play soccer today (11/6) at 15:30 ***COMPLETE***

==Art Museums==

I have two tickets to the Georgie O'Keefe Museum in town and two more to the Harwood Museum in Taos (which is a great little museum). Let me know if you'd like them. ([[Alison Snyder]])

I'd be interested in Georgia O'Keefe! Are they for a particular day/time?? [[Julie Granka]]

==Soccer Field==

If anyone would like to use of the soccer field, please contact [mailto:jp@santafe.edu John Paul] so he can put a request in with conference services. We're not the only event on campus, and St. John's may need to use the field from time to time for other events.

==Squash/Tennis==

Some of you expressed interest in playing Squash and/or Tennis (Mark, Ingrid, Michael,..?). Let's update this section if concrete plans emerge. Also if anyone has information on how/when to use the courts, please post it here.
* Given the fact that I have only black soles, squash is not an option, but tennis would be [[User:Ligtvoet|Ligtvoet]]
* I am interested in playing tennis with anyone, on any day. The hours of the gym are here: http://www.stjohnscollege.edu/campuslife/SF/gym.shtml and I suspect that we can borrow rackets/balls and use the courts during those times. Maybe morning would be a good time, before it gets too hot? ([[Megan Olsen]])

==World Cup Viewing==

It's really more Before Hours, but here in Santa Fe two of the recurring broadcast times for World Cup games are 5:00 AM and 7:30 AM. Is there interest in getting together, either somewhere on campus or--if we're lucky enough--at a local venue to catch a few of the more interesting games before coming to lectures?

*([[Roberta Sinatra]]) Yes, I am very interested. As an Italian, I cannot miss matches of Italy! ;)
*([[Ana Hocevar]]) I guess I might be up for that as well. Especially for the USA vs. Slovenia match. I do count on all non-US participants to root for Slovenia, of course...
* ([[Roberta Sinatra]]) Someone interested in watching the Italy vs Paraguay match, on Monday (June 14th), at 12.30 pm (half after noon, to avoid confusion - 20.30 in South Africa)?
*([[Joseph Gran]]) Definitely going to watch as much of this as possible. Does the tv in the game room get the games?
*([[Kang Zhao]]) Very interested in watching some games!

== Hiking (Baldy this weekend?) ==
There is a whole list of participants who want to hike & climb...

A quick look at the Let's Go guidebook already shows the following options:
* Santa Fe Baldy 8-9hrs hike
* Pecos Wilderness
* Bandelier National Monument - check
* Santa Fe National Forest, Los Alamos - which also has some historic significance = check

I would like very much to hike Santa Fe Baldy. It is a 7 mile journey from the parking lot to the peak with an elevation gain of about 3000ft. Various websites recommend getting off the peak before 2pm to avoid afternoon thunderstorms. This implies (assuming 4hrs to the top and an hour lunch) that we need to start hiking around 8am, which in turn means leaving SJC at about 7:15am (or earlier)! I understand this is a serious commitment, so is there any interest in doing this hike with me?? If so I will acquire a trail map and directions to the trail-head parking lot and any other information that will be useful. Here is a description of the hike -> http://www.santafe.com/articles/climbing-santa-fe-baldy/ ([[Joseph Gran]])

I would be interested ([[Bogdan State]])

== Music ==
Some participants will have musical instruments with them. Join the CSSS house band!

== Concerts ==

=== iron maiden/Dream Theater ===

Anyone would like to go to the [http://www.livenation.com/edp/eventId/419345 Iron Maiden/Dream Theater] concert on June 16 at night, in Albuquerque? Talk to [[Lucas Antiqueira]] if you want company, or if you have any idea on how to come back to Santa Fe late at night.

== SF complex gigs ==

* [http://sfcomplex.org/?m=20100613&cat=11 "off the rails" dance party] this weekend (12th/13th)
* [http://sfcomplex.org/2010/05/steven-miller-in-concert steve miller in concert] on the 11th
* [http://sfcomplex.org/2010/06/mapping-the-complex-a-demonstration-of-ambient-computing that ambient computing show] they mentioned is on the 17th-19th

plus, for bonus geek eyecandy points, the SIGGRAPH show
* [http://sfcomplex.org/2010/06/siggraph-party SIGGRAPH party] this saturday the 12th

== Flamenco ==

Just noticed that there is a flamenco festival in Albequerque. Could be fun ???

*[[Erika Fille Legara]]: I'd love to go! When's this?

== Horseback Trail Riding ==
A few people have come to me to talk horses, and are interested in going on a trail ride if possible. I have a car and could transpot 3 other people. If anyone is interested I can call some places and ask about possible group rates. [[Anne Johnson]]
Hey Anne - if you have any spots left in your car - I would be keen to come [[Ingrid van Putten]]
I haven't gone in years but would love to go. If its the first weekend I would have a vehicle as well. [[Kim Lewis]]
Yes, Ingrid, there's room. Let's talk Friday and decide on a time. Here's a link to one possibility: [http://www.brokensaddle.com/rates.html Broken Saddle Riding Co] [[Anne Johnson]].

There are openings for 4 or 5 riders for Sunday morning or Thursday evening. There is a $35 cancellation fee per person, so I don't want to confirm a resservation until I hear back from everyone interested in going. We need to supply height, weight, and skill level for each rider. There is a weight limit of 200 lbs.
I can try to reserve for Sunday morning (June 13), but they will need all information by 8 tonight (Saturday June 12). If that doesn't work out, we can reserve a Thursday (June 17) evening ride at 6 for either 1 or 2 hours ($55/$80 per person cash, add $5 for credit card). No shorts or sandals, sneakers are OK. About a 40 minute commute from Santa Fe Plaza area. Please email me (amjohnson9@cox.net) your height, weight, and skill level and which rides (either/or) you would commit to going on. We could also look into next weekend. Thanks!

1. Anne Johnson

2. Susanne Shultz

3. Ingrid van Putten (I'd like to go on thursday evening if that would suit...)

4.

5.

== Farmers Markets ==

The [http://www.santafefarmersmarket.com/ Santa Fe Farmers' Market] is Open Every Tuesday and Saturday in the Santa Fe Railyard! 7am-Noon.

It would be cool to go before the Bandelier etc. hike ([[Borys Wrobel]]).

I would like to go this Saturday (June 12)! I have 5 seats in my car, please sign up if you'd like to come! We will eat breakfast at 7:30, and then plan to leave for the farmer's market at 8 in order to be back to leave for hiking at 10.

Andrew's car: 
1.[[Andrew Banooni]] 
2.[[Borys Wrobel]] 
3.[[Bruno Abrahao]] 
4.[[Oana Carja]] yay,sounds lovely! 
5. [[Megan Olsen]] How exciting!! 

[[Borys Wrobel]]: Yes, it was great fun, thanks Andrew! If someone wants to go next week: there's parking close by (underground) for $1/day, you get to taste a lot of stuff (including weird Native American tea, which we pretty much decided is much better w/o sugar), and there was an artist's market across the street.

== Trains! ==

The [http://www.cumbrestoltec.com/ Cumbres and Toltec Scenic Railroad] is one of the longest and most beautiful sections of narrow gauge rail in the US. It is a bit of a hike away, so some car rental might be necessary but it would be awesome!

* exciting! would like to hear more details on what this field trip may be like. [[Anna Pechenkina]]

EDIT: More info!

It seems that we could do this either Saturday the 19 or Sunday the 20. Trains leave every day at 10:00AM from Charma, NM. Charma is about 2:15 hours away by car, and they recommend that you get there 30 minutes early, which means a departure time around 7:00AM. The ride that seems most feasible is the Chama to Osier Roundtrip, which is $75 a person (quite expensive, although it includes lunch if that helps?). The train would get back into Charma at around 4:00PM. I had initially thought of driving out the night before or staying over the night or something, but it seems to me that we could do this as a day trip. I don't have a car but I will figure out how to rent one if people are really interested! More info about rates [https://www.cumbrestoltec.com/schedule-rates/ here]! -- [[Sarah Wise]]

== Rodeo! ==
There'll be a [http://www.rodeodesantafe.org/ rodeo] in Santa Fe June 23-26, the tickets for Saturday Matinee (10 am) are $10. That's more like 'after CSSS' than 'after hours', but maybe someone will be intererested in going? ([[Borys Wrobel]])).

== Board Games ==
I happen to have a nice collection of fun and fairly quick strategic board games. I've talked to a few people who seem interested in getting together from time to time to play some games and unwind. If you think you'd be interested, send me an email or just come up and say hi. I'm thinking our first gathering may be Sunday evening. The games are very easy to learn (so don't be intimidated) and they all exhibit complex behavior (sorry, couldn't resist). Think of it as a fun way to meet people in a new, enjoyable context. [[Drew Levin]]

We should also get people together to play Mafia! It's kind of a card game, and lots of fun. We were thinking Friday night after the SFI reception could be a good time! [[Megan Olsen]]

I'd be interested in this [[Micael Ehn]]

Board games! always fun. Perhaps one of our projects should have been on the effects of being able to use proper nouns in Scrabble. :) ([[Gavin Fay]])

I'm interested [[Michael Szell]]

Games tonight (sunday) in the coffee shop. Late notice but come on by if you're interested. I'll be around... and Andrew brought games too! [[Drew Levin]]

I think I'll just start bringing a few games over to the coffee shop each evening. If you want to play a game, come by and see who's around. There seems to usually be enough people nearby that starting a game should be fairly easy. If you're interested in a longer game, or want to make sure people are around, let me know and we'll work on organizing something more formal. [[Drew Levin]]

== White Water Rafting ==
We are organising a rafting trip down the Class IV Taos box next Sunday the 20th. The Taos box is meant to be very exciting, but still suitable for first time rafters. So far it is my husband and I, but if anyone else wants to join, you're more than welcome. A couple of caveats: 1) it is EXPENSIVE (~$120) and 2) it is all day (which may interfere with projects. However, if this doesn't put you off, please let me know! [[Susanne Shultz]]
* I'd love to go! [[Micael Ehn]]
* CLass IV eh? [[User:Ligtvoet|Andreas]]

==Sandia Peak Tramway==
The longest tram in the world is only an hour away from us. The tram takes you up to the top of Sandia Peak (elevation 10,378ft, 3,163m) where there are various hiking trails and scenic viewpoints. The tram operates until 9pm everyday of the week and costs $20 per person. Anybody interested in going? How about next Friday evening (or any other time), we could eat dinner at the Mexican restaurant (Sandiago) in the tram lobby. link-> http://www.sandiapeak.com/ ([[Joseph Gran]])

[[Micael Ehn]] Sounds like fun!

Count me in! [[Bogdan State]]

==Bandelier Hike / Valles Caldera / Los Alamos ***COMPLETE***==

Tom, JP and others are planning a field trip to [http://www.nps.gov/band/ Bandelier National Monument] for Saturday June 12. [[Bandelier Trip 2010| Please sign up]] so we know how many people are going.

We'll depart the parking circle at <strike> 8:00 </strike>10:00 am, head up to Bandelier to do some hiking <strike>before it gets really hot</strike> when it's really hot, then head up to the [http://en.wikipedia.org/wiki/Valles_Caldera Valles Caldera] and Jemez Caldera in the early afternoon. A trip to the [http://www.lanl.gov/museum/ Bradbury Museum] in Los Alamos will finish the sightseeing, and then maybe dinner in Santa Fe?

==El Farol Field Trip***COMPLETE***==

A few people were interested in "making a pilgrimage" to El Farol. Any takers?

I think it would be fun to do after the SFI day on Wednesday. Let's plan ~ 6:00, depart by walking from SFI? It's about a mile and a half. ([[jp]])

* Did I miss this? If so, there should be another one. It's not really a valid homage to the paper if there are not iterated plays! ([[Lynette Shaw]])

==Aaron Clauset's Lecture***COMPLETE***==

SFI Omidyar fellow Aaron Clauset will be presenting a talk entitled "[http://www.santafe.edu/gevent/detail/public/103/ The Future of Terrorism]" next Wednesday at 7:00pm. [[Sign Up for Aaron's Lecture | Please Sign Up]] if you'd like to attend so that we have an idea of how to organize transportation.

VLA signup

2010-06-17T05:55:32Z

Sergey:

{{CSSS 2010 Santa Fe}}

Wanting to go to the VLA on Saturday 19th June? Put your name down below. usual carpooling thing....

*'''Anne Johnson''' (3 other seats)
# [[Gavin Fay]]
# [[Borys Wrobel]]
# [[Ingrid van Putten]]

*'''Needing wheels'''
# [[Micael Ehn]]
# [[Ana Hocevar]]
# [[Sergey Melnik]]

CSSS 2010 Santa Fe-Blog

2010-06-15T03:55:56Z

Sergey:

{{CSSS 2010 Santa Fe}}

Use this page as an informal forum to share your opinion and discuss anything at CSSS'10.

* [[Michael Szell]]: Some people asked me about the URL of my online game. Here it is: http://www.pardus.at - Enjoy! :) (The tutorial may some time to complete..)

* June 7 ([[Ana Hocevar]]): So I know my official day of contribution on the blog is not until tomorrow, but I wanted to share this with those who are interested. When I get inspired by someone giving a good talk, I have a tendency to write down some of the statements I find encouraging or funny and so on. So here are my favorite quotes from the first day of lectures (and I hope the lecturers don't mind this):

"If there is one thing you should learn at the summer school, it's to speak up." -Dan Rockmore

"Science is a social thing." - Dan Rockmore

"You start with a beautiful idea and end up with reality." - Dan Rockmore

"Commit to taking advantage of this opportunity." -Dan Rockmore

"Let it all marinate up there." -Dan Rockmore

"And wear sunscreen." -Ginger Richardson

[[Dan Rockmore]]: Here is a link to the NYR piece I mentioned today
http://www.nybooks.com/articles/archives/2010/jun/24/other-side-science/
Good to meet you all and looking fwd to a great CSSS.

==Monday June 7==
Maria Opazo 

===Alison Snyder ===

I thought it might be interesting to give my perspective on today as a journalist and writer. What I starred and underlined in my notebook, what stuck in my head and why.

First as a journalist…

Schooling Fish

I’m familiar with some of Iain’s research – the beautiful images and descriptions of phenomena that many curious people outside the sciences have seen and thought about lends itself to visual storytelling -- but today was the first time I heard him discuss his fish work. In particular, I’m going to follow what he’s looking at in terms of how individuals influence others in the group and the (preliminary?) finding that some individuals consistently influence the group. Because it is unpublished, I’ll check in with him periodically to discuss in more detail and see how the research is progressing as well as whether and when he might expect to publish the research.

Moiré-ing

Have you ever seen someone on TV who's striped shirt competed with the gravity of what they were saying? In TV production we pay editors large amounts of money for hours of work to fix moiré-ing so the term “numerical moiré-ing” caught my attention.

Chaotic Mixing

Liz mentioned her CU colleague who described clams that open up to exploit chaotic mixing to mix up their gametes. The counterintuitive idea of systems not only embracing chaos but exploiting it, is a provocative theme to explore in a general audience story. To most people, chaos is something to be avoided.

Ideas that got my attention as a writer…

Gas Gauges and Indelible Images

In opening her lecture, Liz used the metaphor of her old car’s gas gauge to illustrate non-linearity. The gauge stayed on full then plunged when the tank was near empty rather than dropping as the gas level dropped. While it was a brief aside about a concept that is very easily understandable to a scientist, it might not be to a non-scientist. To someone who has never heard of or thought about non-linearity, they will understand it the first time they hear this metaphor and they’ll remember it. Even if they forget what the gas needle was illustrating, they can back track. Non-linearity becomes an indelible idea.

As a writer, the metaphor also reminded me of the power of a simple idea in telling a story. One of the most difficult tasks is parsing the scale of what a story is about. Sometimes the most meaningful way to tell a story about the Empire State building is to describe one of the bricks.

In other words, today was full of lots of ideas about research to follow and reminders about how to effectively communicate even the most basic of ideas and the power of doing just that.

Looking forward to tomorrow…

===Kyla Dahlin===

My notes from today are mostly graphs, equations, and Dan's quoted quote about "what if biologists had tried to develop a theory of gravity." I'd love to see a debate between the math/physics/universality camp and the biology/ecology/sociology/everything is different camp. Seems like an interesting tension within Complex Systems folks.

So far the self-organization into project groups seems to be going well, and I'm sure it will evolve over time. Tonight a few of us talked about the pressure to collaborate being somewhat foreign - so much of PhD work is so solitary. I'm sure the sociologists would love to track the networks that are forming, the different players, and our final results.

And I think we all are trying to maintain a balance of fun, thinking, working, and staying level in a world with constantly flowing coffee.

===Lucas Antiqueira===

Some first impressions:

This first day of lectures was really nice. I was exposed to subjects I'm not quite familiar with, lectures were excellent and inspiring, projects started to evolve. The process of getting to know people continued, there are so many brilliant minds here.

The summer school is a dream coming true for me. I've been in Santa Fe for only a few days, and I can definitely tell that these days are among the most gratifying in my academic life. And things have just begun!

Many thanks for the SFI/St.John's staff for the support! Not to mention the food, which is excellent by the way!

==Tuesday June 8==

===Andrew Banooni===
Some of you have heard me use this analogy, and I’m certain that many others of you have heard it elsewhere, but they say that the amount of material there is to learn in medical school is a bit like trying to drink water from a fire hydrant. One thing that I had not realized until attending yesterday and today’s lectures, however, is how homogeneous that information seems, now that I’ve gotten a taste of the multidisciplinary approach here at SFI. Sure, there are a tremendous number of disease processes that involve vastly different physiologic systems, and don’t even get me started on all the bugs and drugs we have to learn, but it’s all medical. We don’t sit and discuss econometrics (actually I don’t think I’ve ever had a discussion about econometrics), or the influence of individual fish on collective behavior. Over the past two days, I’ve dusted off cobwebs from parts of my brain that I feel I haven’t used in years. I don’t mean to say that I am rusty in certain topics (and completely new to many others), but rather that I feel that in the past 48 hours I have been thinking in ways I haven’t had to think in my graduate training. In medicine, you can survive by learning a tremendous number of facts and then regurgitating them at the appropriate time. We observe, we recognize patterns, we diagnose, we treat. I am so thankful for this refreshing reminder that there is so much more enrichment to be had, that the medical problem I am trying to solve can share many similarities with a physical, financial, or aeronautic one my colleague might be struggling with. I feel inspired by every one of you, very lucky to be here, and I look forward to three amazing weeks!

===Andreas Ligtvoet===
====Liz====
* It's a skill to explain difficult stuff in an easy way.
* Lots of dusting off of things I should know, but forgot.

====Peter====
* Some interesting discussion about the end of theory due to access to large amount of data. It doesn't help you understand stuff, though.
* Walmart seems to have enormous amounts of data. A colleague of mine suggested finding ecologies of consumer products. What type of furniture goes best with red napkins?
* We can create huge amounts of non-existant networks and have fun with them.
* An average node degree of about 4 leads to hairballs. What can we do with those?

====Iain====
* The larger the group of naive individuals, the (relatively) easier it is to influence it. For 10 individuals you need 50% 'leaders', whereas for larger groups only a few %.
* Another interesting remark either yesterday or today: just because you have a nice model for some fish species, doesn't mean you can apply it to cows or bugs or. ..
* THe details of the system do not matter in a collective transition.
* As soon as you behave differently, you are nailed.

====Tom====
* How much to put in a model? Not too much, says Tom. However, what good is an "economic" model that shows a Bolzman distribution? His answer is that this is a natural law in other words, you will never make an economy where the Bolzman distribution does not exist. It is even worse if you allow people to invest.
**In the state of Ilinois, Pi was legally defined as 3.
**Stochastics from στοχαστικός, from στοχάζομαι ‘aim at a target, guess’, from στόχος ‘an aim, a guess’.
**Mention power law and get published!
*Immunize Pig/Mexican/Flu: make use of power law in a network => your friends are more connected than you are! Fascinating...
*We don't know all that much about networks: we don't know what matters.
*Agents with genomes: 10010101. DIstribution split of genome crossover matter!
**T-shirt sniffing leads to selection of different immune systems.
*In complex systems there is a lot of exploratory stuff.
*Tom is a (scientific) heretic.

====Drinks====
@Cowgirls. What's this ID thing about anyway? Don't I look old enough?

===Xin Wang===
The topics today are involved in nonlinear dynamics, complex networks and collective behaviors. I am very interested in those topics before this summer school, and through lectures I get the deeper understanding about those three areas.

But what impresses me most is that the students here are very active and it is different from the situation in China. In the meantime, I enjoy the joy of communicating with people from different backgrounds and getting cross-field collaboration.

===Ana Hocevar===

I am not a blog person really, I've never written a blog before, but I guess CSSS is also a great opportunity for trying out new things unrelated to science. So, here I go.

As many others, I can't get over how amazing Iain Couzin's talks were. I am very impressed and greatly inspired. Usually attending physics conferences that left me wondering what it was that I was missing, Iain I think made me realize I prefer systems that include things with eyes and wings. Or perhaps gills? Amazing work in my opinion, really.

I should also thank Liz Bradley for giving incredibly clear lectures on nonlinear dynamics. From the courses I had on chaos, I wouldn't imagine such an intuitive presentation of the topic is possible. It certainly isn't easy, so: Liz, you rock!

I haven't been enjoying only the lectures, though. Dancing to no music with Andrew, listening to Jonathan playing the violin, stimulating discussions over lunch or breakfast, great food (we even have ice-cream!) and so much more...

So with such great company, such cool science and so many wonderful things still ahead of us, I can only say I am very grateful to be here.

===Borys Wrobel===
I will not be the first to say that Liz Bradley's lectures are something to behold. I am constantly taking notes on not what she explains but HOW she does it. Especially the mix of powerpoint and whiteboard/transparencies. Hopefully I can decipher my handwriting when it comes to explain some of this stuff when I am teaching. Iain Couzin's are also very inspiring, especially on the advantages of keeping things simple. It was even more inspiring to talk to him @cowgirls, especially his views that it is important to discourage grad students/postdocs to keep TOO long hours... and the importance of having a 'fun lab' in attracting people that would like to work you. It was fascinating to see how Tom Carter engages the audience, so late in the evening (and after dinner, too!). I am not sure that we Europeans agree on his view on how the economic inequalities can be addressed, he seemed very pessimistic about the possibility of it, and many people in the room, I think, were asking themselves how introducing taxes etc. would affect the distributions.

===Other remarks===
Some people may be interested in the http://decoi.collectivae.net/ Design Of Collective Intelligence series - those are 1 week long versions of what SFI is trying to do, but mainly focused at multi agent systems.

Also interesting, and this is even a longer shot, is http://www.nextgenerationinfrastructures.eu/academy if you are interested in (physical) networks and infrastructures.

Here is an article about the spread of contagion in a social network written for a general audience, as an example of science journalism:

"Infectious Personalities", The Economist, May 13, 2010. http://www.economist.com/node/16103882

AS

==Wednesday June 9==

Today was a sad day for Dutch politics. [[User:Ligtvoet|Ligtvoet]]

 Thank you Paige and Coco. [[Samuel_Scarpino|Samuel_Scarpino]]
 Great Kerouacish moment. Thanks hairy thighs! [[Giovanni Petri]] 

([[jp]]) Man, I don't know what went on last night...

===Ingrid van Putten ===
Lots can be said about the visual art - but the bar has definitely been raised by mathmeticians and computer geeks over the past two days at SFI. Not only did we have buildings tumbling down or having fish swim out of them at the Santa Fe Complex last night, but today liz completely outdid the lot by making music and then ... dance. Those performances should make maths, physics, and computer science interesting to anyone!

===Thomas Maillart===
This morning Peter told about network attack tolerance. The results obtained by Albert et al. Nature (2000) for scale-free networks are a direct consequence of the "robust yet fragile" (also called HOT - Highly Optimized Tolerance) concept first coined by Carlson et al. Physical Review Letters also in 2000. However, Newman et al. criticized the HOT model (in Physical Review Letters, 2002), arguing that while "optimized", scale-free systems, the optimization process should occur at some costs. Thus, they introduced the COLD model ("constrained optimization with limited deviations"), by adding a cost to optimization (i.e. preventing the formation of scale-free systems). Under these conditions, the tolerance to attacks should be improved. The interesting point behind the message, is that there is an intrinsic trade-off between optimization and risks, i.e. optimized systems are prone to suffer more extreme damage (heavy-tailed distribution of damage).

On the same topic, Doyle et al. (PNAS 2005) argued that the model by Albert et al. (Nature 2000) does not hold for the Internet because the most connected nodes are not in the core of the Internet, which is typically low connected. The main point of this article is to point the importance of looking at the mesoscopic structure of real networks, and not only their degree distribution or general purpose metrics.

===Vessela Daskalova===

Some thoughts inspired by Tanmoy Bhattacharya's lecture on inference in historical processes and by Tom Carter's modeling workshop:

They both tackled two classical questions regarding the methodology used in different fields.

1) Are we trying to explain past observations or are we trying to predict future events? And how do models in different fields reflect this goal?

2) Do we want to build in what we already "know" in models we are building/ regressions we are running?

Obviously, people from different fields will answer these questions differently. It would be cool if at least one person from each field wrote about what is accepted in their area.

Here one point of view from economics:

on 1) In contrast to historians, who try to give a good explanation of what happened in the past and why, economists try to make some predictions regarding the future. Therefore, models/regressions in economics include fewer variables than models/regressions in history and political science. Tanmoy Bhattacharya argued in favor of including many explanatory variables when using maximum likelihood for historical inference. However, if the goal was prediction rather than inference, the number of explanatory variables would have to be reduced to avoid introducing a lot of past noise in the predictions.

on 2) In the social sciences (especially economics) there is a tendency to build in some assumptions of what matters in your model. This seems useful (at least to me) as many of the phenomena we are analyzing are a result of social interaction, there is a large degree of randomness in the environment and unless we use our a priori knowledge (as Tanmoy Bhattacharya argued yesterday), we cannot expect to come up with some deterministic equation that accounts for social phenomena.

Coming back to prediction in economic models, let me end with a popular economics joke:
"Why do meteorologists make weather forecasts?"
"To make economic forecasts look good."
Just to clarify, this is not meant as an insult to meteorologists, but as self-irony:)

===Kasia Samson=== 

===Borys Wrobel===
It is really too bad that Peter Dodds did not have the time to present his last lecture, I was really interested in hearing it. I feel this was the cost of the historical perspective (his first lecture)... Santa Fe Complex sure was fun, it sure seemed a geek paradise. It was great to see the American culture of innovation at its best... But it sure was a grueling day, having to get up earlier than on the other days, running to the buses, going from one place to another. Not enough time to explore the SFI (and its library) really, hopefully it will be possible next Wed... It is amazing that so many people decided to stay late at night and walk back to St John's...

==Thursday June 10==
===Chaitanya Gokhale ===
"The trick about life is to make it look simple."

It would seem quite ironic if I say this at a “complex” systems summer school, but the more I get immersed in the subject the more I think that it is relevant statement.
I mostly apply nonlinear dynamics to develop mathematical models of biological system and apply evolutionary game theory to biologically, socially relevant concepts. Please note that both of these is not data driven to begin with.

Oxford Dictionary defines “model” as follows (model in the context as we use it),

...3 something used as an example. 4 a simplified mathematical description of a system or process, used to assist calculations and predictions. 5 an excellent example of a quality....

A model is not the actual system.
Tom Carter gave an amazing demonstration of that fact. The models he was discussing were not of as much importance as the message he was trying to put across. We do not need complex models to understand complex systems, rather simple models is what we should be aiming for because the goal is not to replicate the complexity but to understand it in simpler terms.
The same thing was iterated by Owen Densmore at the SF Complex and saying that what they are doing is complex would be the biggest understatement.
Today again Jure just amazingly deflated the whole network complexity into a simple 2 \times 2 matrix confirming the idea ever more.

Any fool can make things bigger, more complex and more violent. It takes a touch of genius and a lot of courage to move in the opposite direction
--Albert Einstein

On a different note, I loved Liz Bradley’s lectures. Though I have been using the methods for quite a while now, I had never seen such a crystal clear overview of nonlinear dynamics before.

===Jing Li ===
When Google first topped the 100 best companies to work for, Fortune's comment was 'It's the kind of place where, yes, you're going to work but you also know you are going to have a fun time as well'. I would like to say exactly the same for CSSS 2010.

What a beautiful day today! Liz's final presentation is as excellent as previous: science is not only interesting, but also COOL; Nathan is as impressive as his project at CSSS; Jure is so passionate about his research. Dan, your comment is the highlight of the presentation, as always.

A friend of mine who was in CSSS 2009 wrote 'I hope your time at SFI is as wonderful for you as it was for me'. Yes, it is!

Bradford Cross has a great [http://measuringmeasures.com/blog/2010/6/9/learning-about-network-theory.html post] on learning about network theory that everyone with an interest in networks will probably find useful. Look at it or bookmark it for later, it compliments our previous lectures well.

The CSSS hash tag on twitter is #CSSS, the REU tag is #SFI.

===Bruno Abrahao ===

One of the recurring themes in our lectures was power-laws in the degree distribution of complex networks. Since this feature was so prevalent across different networks, coming from many different domains, researchers started to create generative models that replicate this observation, with the goal of shedding insight on the root cause of this phenomenon. Some of the plausible explanations include preferential attachment, the copying model and others.

In 2004, [http://conferences.sigcomm.org/sigcomm/2004/papers/p599-li.pdf Li-Alderson-Willinger-Doyle] made the point that observing a power-law does not give us any insight on the underlying phenomenon. They show that a large number of different networks, with dramatically different characteristics, exhibit the same power-law behavior with the same power-law exponent. The paper was very well received by the computer systems community (it received the best paper award in the top conference in the area, ACM SIGCOMM), but it seems to be often ignored by other communities.

To make matters more complicated, [http://www.eecs.harvard.edu/~michaelm/postscripts/im2004a.pdf Mitzenmacher] made the point that it is virtually impossible to distinguish any generative process that exhibit power-law behavior from those that exhibit lognormal distribution.

Can we conclude that power-law observations must be accompanied by some form of validation of the root cause of the phenomenon in order give us useful information on complex systems?

=== Anna Pechenkina ===

Thanks, Bruno, for bringing this up! Networks are new to me, but the published findings of power laws in agent-based models is something that I've come across quite a bit. The question of model validation seems to lack a good answer (and expected practice, which is true at least in political science). If a model generates a power law distribution of some parameter of interest, normally, people do check for robustness of the finding. However, even when the model produces the power law across a large portion of the parameter space, this is no guarantee that the model is a good model of the phenomenon of interest (Tom Carter mentioned on Tues finite vs. infinite variance). The fact that there may be other ways to reach the same power law distribution calls for some sort of validation of the model's mechanism. I would like to hear what others believe a good example of "validation of the model's mechanism" can be (testing the model's *additional* implications against observational data? designing a test of whether the subjects use indeed the decision-making rule specified in the model? modeling different decision-making rules?) Cites of good examples are much appreciated!

=== Griffith Rees===

Agent-based modelling is still a pretty new thing in sociology, and validation has always been a weak suit. Peter Hedström has [http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=0521796679 attempted] to mix empirical results with simulations to assess the relative impact of different effects, and the extent to which they explain macro phenomena. In his case, he is modelling diffusion of unemployment, and the extent to which being socially tied to other unemployed people increases your likelihood of becoming unemployed and increases the length of your unemployment. I don't think his validation really does the job, but it's an interesting approach.

==Friday June 11==
([[Kang Zhao]])
I really like what Nathan Eagle's idea of Engineering Social Systems. Yesterday was the 3rd time I heard his talks. I feel that, in the emerging area of network science, people have been focusing mainly on understanding the patterns in all kinds of large networks. No offense to those outstanding research. But... OK, power-law distribution, highly-clustered social network, 6-degree of separation, then what? I have engineering background and always love research that can make a difference in the real world. Can we build more applications to exploit the network structure/pattern to make people's life better/easier? While there have been some efforts (such as the [https://networkchallenge.darpa.mil DARPA network challenge] this year) and interesting applications, I don't think network science is quite there yet. (Of course, we need to keep privacy issues in mind when we mine social network data).

===Florian Sabou ===

A recent article in The New Yorker, "Silver or lead" by William Finnegan, reveals the deep complexity of the drug war reality in Mexico. Rather than a typical armed conflict between authority and drug gangs, or between gangs themselves, the violence in Mexico presents characteristics of political, social and religious insurgence. Drug gangs offer public services that the central government fails to implement such as: construction of community sport and art centers, administration of justice, unemployment management, security and even drug-rehabilitation clinics for methamphetamine addicts. An overview of the article can be found at
http://www.newyorker.com/reporting/2010/05/31/100531fa_fact_finnegan and for interested readers the printed magazine issue is available. 

===Roberta Sinatra===

… and so this first week at CSSS is over. And it has been a very "intense" conclusion indeed!
I would like to make a couple of comments/reflections, scientific and not:

* Leskovec lectures and the need of large dataset analysis: at the conference NetSci2010, László Barabási stated that "by 2023 the number of stored bits will surpass Avogadro's number". In my opinion, if this is true, no matter how good will be our tools for the large scale analysis, we will never be able to deal with a "microscopic" description of data. In the same way, for example, we are not able, and anyway it will be not that useful, to describe all the molecules in a gas using their dynamical equations, but we can just deal with the statistical ensemble of all the possible configurations they occupy, and study the constraints the system meets and the properties that derive from them. Therefore, what probably we will need in the future, is try seeking in all our data generality and common features as well as analogous constraints, by looking at them as realizations of a big ensemble of possibilities that are all equivalent, in some sense, and could share the same properties.

* Hübler lecture: I enjoyed it so much! I have a background as a physicist and because of this I attend a lot of "lab courses"during my studies. Nevertheless, since I work on complex systems, I had never the chance to enjoy them from a pure "experimental" point of view. The opportunity to go to the lab with him will make us figure out that complex systems are much more of a bunch of data someone collects for us, but they are most of the times systems we can reproduce. ANd much better if these experiments are eatable ;)

* Power cut during the lectures: are we still able to teach or give a lecture without the use of slides, but just with a piece of chock and a blackboard?

* The dinner at the Santa Fe Institute has been very pleasant and I really appreciate its familiar, welcoming and friendly atmosphere. And a proof of this is given by the fact that a cat that lives there in the same way he could in one of our houses! (By the way, never seen a cat in a research institute! Do you?)

* Mafia game of friday night: some of us played for 4 hours (yes, 4 hours!) the famous - but not to me - [http://en.wikipedia.org/wiki/Mafia_%28party_game%29 mafia game]. It was a very good opportunity to socialize with other people, because when far from lectures and "working" hours, none of us feels he has to "prove" to be smart and brainy, and it is easier to be natural and spontaneous.

===Bogdan State===

I sure hope no one got annoyed at my hunting for candid pictures today at SFI. I am a very awkward person, which makes my tries at being a photographer...well, awkward. So thanks to everyone who smiled and went along with my snapshot-happy self. I hope seeing the picture will make you more tolerant of the annoying guy with the pesky lens:

http://picasaweb.google.com/worldmeetsbogdan/SFIBarbeque#

As for the CSSS, I'm in total awe of the program. This week of lectures has felt overall like gym for my brain - particularly all the advanced math in Liz's class. Hopefully, brain gym will be easier to keep on a schedule than other kinds of gyms...cough...

===Bruno Abrahao ===

This is a timely analysis of an interesting complex system. I personally like his results! ;-)

[http://www.news.cornell.edu/stories/June10/SoccerBlog.html Cornell University professor predicts Brazil will win 2010 FIFA World Cup title] His soccer study submits world's best teams to statistical analysis.

===Lucas Antiqueira ===

Nature's article: [http://www.nature.com/news/2010/100609/full/465674a.html High hopes for Brazilian science]

===Complex Emergence===
Hübler: "So, definitions of complex systems? " 
Erik van den Broecke: "Female." 
Sarah Wise: "Clearly you never dated a male" 

 

Hübler: "If an ant would ask you to teach her calculus, what would you tell her? You would tell her, sorry little ant, that's a noble request, but you just don't have enough neurons!"

==(Saturday June 12)==

Simple Pleasures:

Rides from Leroy (and Paige/Coco)
Proper Espresso
Griff's Parkour
Dutch Heaven
Gold Ones
I study English long time
Evolution of Secondary Sex Characters in Northern Europe
"If I were only at sea level . . . "
"I'm putting that on the blog"

==(Sunday June 13)==

"Do you want me to clear my cache?" -Tom Carter

"NO! NO! NO! NO! NO! NO!" -Everyone

==Monday June 14==

===Andrew Hein===
I spend a lot of time using the statistical programming language, R. Although, it is a pretty poor platform for implementing the type of agent-based and network models that most of us are using, it does have some nice network statistics packages among other things. One great resource for R users is the R-seek search engine [[http://www.rseek.org/]]. If you're interested in network statistics, just head to R-seek and search "networks". There are a bunch of network stats packages.

Tracey McDole 
===Sergey Melnik===
It seems that today there were particularly many people sneezing and coughing. Is there a disease spreading through our population? Apparently the extensive exposure to the sun during the weekend has had a negative effect on students' immune systems. We should be more careful with such things and really try to remain healthy.

''Bus paradox:'' The mean waiting time for the next bus (for highly irregular service) is greater than the mean interdeparture time. This is because it is more likely to hit a long interdeparture time than a short one when arriving at the bus stop at random. So keep this in mind.

Erik Van den Broecke 

==Tuesday June 15==
Drew Levin 
Leif Karlstrom 
Mark Laidre 
Borys Wrobel 
==Wednesday June 16==
Joseph Gran 
Micael Ehn 
Damian Blasi 
Daniel Jones 

==Thursday June 17==
Yixian Song 
Sam Scarpino 
Giovanni Petri 
Michael Szell 

==Friday June 18==
Sandra Bennun 
Susanne Shultz 
Lynette Shaw 
Sarah Wise 
==(Saturday June 19)==
==(Sunday June 20)==

==Monday June 21==
Dan MacKinlay 
Megan Olsen 
Vanessa Weinberger 
Jonathan Cannon 

==Tuesday June 22==
Erika Legara 
Gavin Fay 
Bruno Abrahao 
Zhiyuan Song 

==Wednesday June 23==
Julie Granka 
Nick Foti 
Felix Hol 
Oana Carja 
==Thursday June 24==

==Friday June 25==

Alfred Hubler's Nonlinear Dynamics Lab 2010

2010-06-14T23:40:08Z

Sergey: /* Monday June 14, 6:00pm */

{{CSSS 2010 Santa Fe}}

Alfred will be hosting a lab where students get to play around with a few experiments in nonlinear and chaotic physics.

Class size is (roughly) limited to 15 students.

==Monday June 14, 6:00pm==
1. [[User:Dan90|Dan MacKinlay]]

2. [[Nick Foti]]

3. [[Lucas Antiqueira]]

4. [[Rajani R. Shenoy]]

5. [[Zoe Henscheid]]

6. [[Gavin Fay]]

7. [[Damian Blasi]]

8. [[Anna Pechenkina]]

9. [[Andrew Banooni]]

10. [[Sergey Melnik]]

11. [[Erika Fille Legara]]

12. [[Thomson McFarland]]

13. [[Kimberly Lewis]]

14. [[Anne Johnson]]

15. Louis Lerman

==Tuesday June 15, 6:00pm==

1. [[Drew Levin]]

2. [[Massimiliano Spaziani]]

3. [[Eric 'Siggy' Scott]]

4. [[Ana Hocevar]]

5. [[Joe Gran]]

6. [[Kang Zhao]]

7. [[Oana Carja]]

8. Louis Lerman

9. [[Bruno Abrahao]]

10. [[Kyla Dahlin]]

11. [[Ingrid van Putten]]

12. [[Megan Olsen]]

13. [[Chaitanya Gokhale]]

14. [[Zhiyuan Song]]

15. [[Jonathan Cannon]]

==Wednesday June 16, 7:00am==
 PLEASE NOTE THAT THIS IS AN EARLY MORNING CLASS 

1. [[Daniel Jones]]

2. [[Katarzyna Samson]]

3. [[Griffith Rees]]

4. [[Susanne Shultz]]

5. [[Erik Van den broecke]]

6. [[Tracey McDole]]

7. [[Vessela Daskalova]]

8. [[Yixian Song]]

9. [[Neal McCollom]]

10. [[Michael Szell]]

11. [[User:Ligtvoet|Ligtvoet]]

12. [[Vanessa Weinberger]]

13. [[Pilar Opazo]]

14. [[Roberta Sinatra]]

15. [[Borys Wrobel]]

==Thursday June 17, 6:00 pm==
1. Jing Li

2. [[Micael Ehn]]

3. [[Thomas Maillart]]

4. Xin Wang

5. [[Lynette Shaw]]

6. [[Sarah Wise]]

7. [[B. Shiva Mayer]]

8. [[Giovanni Petri]]

9. [[Samuel Scarpino]]

10. [[Felix Hol]]

11. [[Leif Karlstrom]]

12. [[Florian Sabou]]

13. [[Julie Granka]]

14. *GUEST*Quan Bui

15. Rick Boggs

16.Louis Lerman

17. [[Andrew Hein]]

Bandelier Trip 2010

2010-06-11T14:17:58Z

Sergey: /* Julie's Funmobile: 5 seats */

Please sign up here so we know who's going. 
Also: If you have a car, please let us know. The more cars, the more people. 

We'll meet at 10:00am in the parking circle.

Please remember to bring a hat, sunscreen, water, hiking shoes, and anything else you'll need for a day out in the field.

==Cars:==

===John Paul's Camry: 4 (maybe 5) seats===

1. [[John Paul]] 
2. [[Sarah Wise]] 
3. [[Micael Ehn]] 
4. [[User:Ligtvoet|Andreas]]

===Tom's Sedan: 4 seats===
1. [[Tom Carter]] 
2. [[Kang Zhao]] 
3. [[Yixian Song]] 
4. [[Borys Wrobel]]

===Joe's Corolla: 4 seats===
1. [[Joe Gran]]

2. [[Roberta Sinatra]]

3. [[Michael Szell]]

4. [[Chaitanya Gokhale]]

===Andrew's SUV (5 seats)===
1. [[Andrew Banooni]] 
2. [[Zhiyuan Song]] 
3. [[Anna Pechenkina]] 
4. [[Ana Hocevar]] 
5. [[Erika Fille Legara]]

===Max's Car: 4 seats===
1. [[Massimiliano Spaziani]]

2. [[Florian Sabou]]

3. [[Gavin Fay]]

===Julie's Funmobile: 5 seats===
1. [[Julie Granka]]

2. [[Oana Carja]]

3. [[Susanne Shultz]]

4. [[ Sergey Melnik]]

==Still Need Rides==

Sign Up for Aaron's Lecture

2010-06-11T05:11:11Z

Sergey:

Sign up here if you'd like to attend Aaron Clauset's lecture.

Once we have a rough idea of how many would like to attend, we'll either organize our own transportation or rent a few shuttles.

1. [[John Paul]]

2. I'll be there, but I won't need transportation. [[Thomson McFarland]]

3. Also attending, but will not need transportation [[Kim Lewis]]

4. [[Oana Carja]]

5. I am interested and need transportation. [[Kang Zhao]]

6. Bruno Abrahao - attending and need trasportation

7. Me too, need transportation...[[Yixian Song]]

8. Will not need transportation [[Rajani R. Shenoy]]

9. Will not need transportation either! [[Zoe Henscheid]]

10. Can provide transportation for 4 other people. [[Andrew Banooni]]
<pre>Andrew, hi, may I ride with you? - Erika Legara</pre>
11. Need transportation [[Megan Olsen]]

12. [[Alison Snyder]]

13. Need transportation. [[Anna Pechenkina]]

14. Need transportation [[Erika Fille Legara]]

15. Need transportation [[Damian Blasi]]

16. Would like to go, but need transportation [[Micael Ehn]]

17. Need transportation [[Sergey Melnik]]

Network's shortest paths

2010-06-11T05:00:56Z

Sergey: New page: ==Network's shortest paths== '''Team''': Sergey Melnik, Roberta Sinatra, Bruno Abrahao, Michael Szell, Drew Levin Consider a random network consisting of ''N'' nodes ...

==Network's shortest paths==

'''Team''': [[Sergey Melnik]], [[Roberta Sinatra]], [[Bruno Abrahao]], [[Michael Szell]], [[Drew Levin]]

Consider a random network consisting of ''N'' nodes where each pair of nodes is connected with a given probability ''p'' ([http://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model see Erdos-Renyi random graph]). The question is about the shortest path through the network from one node to another (also called geodesic path, or intervertex distance):

Can we calculate analytically (and exactly) the probability distribution of shortest paths in such a network? That is, how likely it is that a pair of nodes chosen at random will be distance ''D'' apart. For distance ''D''=1 the answer is obviously ''p''. What are such probabilities for distances ''D''=2, ''D''=3, ''D''=4, etc.?

Note that the network has a finite number of nodes (which is not necessarily large) and there are only 2 parameters here, ''N'' and ''p''.
This is a simple yet fundamental question and there is much more to follow in terms of immediate applications and new theories once we answer it.

CSSS 2010 Santa Fe-Projects & Working Groups

2010-06-11T04:49:25Z

Sergey:

{{CSSS 2010 Santa Fe}}

[[Working Group Wiki Scratch Page]] 
* [[Structure-dynamics interplay in complex networks]]
** [[Dynamic Architecture of Networks]]
* [[Networks Coalitions and Revolutions]]
* [[Smart Leadership]]
* [[Gossip]]
* [[Evolution/genetic algorithms]]
** [[Evolutionary dynamics of structured genetic algorithms]]
** [[Genes for Breakfast]]
* [[Social Modelling Working-Group]]: non-project specific
* [[Devils and Roadkill]]
* [[Mobility in an online world]]
* [[Beyond Tit-for-Tat: overall profit on spatial evolutionary games]]
* [[Volcanoes, Adoption, Fish: analysis of spatially and temporally nonuniform data series]]
* [[Grouping behavior and the evolution of animal migration]] '''looking for help from a CS'er!'''
* [[Anomalous diffusion on complex networks]]
* [[Brainstorming for Smart Grid Analyses]]: everyone?
* [[Evaluation of strategies for fitness-driven random walkers on a graph]]
* [[What's Happening?]]
* [[Network's shortest paths]]

== Systems failure in corporate networks ==

members: Bruno Abrahao, Pilar Opazo, Nicholas Foti, Roberta Sinatra, Oana Carja

== Evolution of Words==
(Dan Rockmore) - In a class on complex systems that I teach at Dartmouth one of the final projects seemed to indicate from a small and somewhat biased sample of English words, that word origins (as indicated by one of the online dictionaries) seem clustered at certain times. As a start I would propose a mining of this info in some online dictionary, performing some initial analysis and see if "there is a there, there.." and if so, keep on going.
http://tuvalu.santafe.edu/events/workshops/index.php?title=CSSS_2010_Santa_Fe-Projects_%26_Working_Groups&action=edit

== Dynamics of Equities Market Structure ==
(
Dan Rockmore) -- In a paper of mine w/some of my buddies (some of whom you will meet this summer), "Topological Structures in the Equities Market," PNAS December 30, 2008 vol. 105 no. 52 20589-20594, we found some interesting structure in the correlation network of the NYSE equities market. This required a choice of a time window. It would be interesting to see how/if this structure changes over time and window size, especially on either side of market crises. Scott Pauls has code that could be used to do some of this analysis.

== Style of Chess Play ==

(
Dan Rockmore) -- I am curious to see if using tools from learning one can characterize the "style" of a chess player. The website www.playchess.com has a database of chess games. I'm not sure if the annotation would enable the determination of particular players, but even without that, can clustering on the move data give sensible/interesting results with respect to style of play?

== Trusting Swarms ==
see [[Trusting Swarms]] (Bruno Abrahao, Zhiyuan Song, Bogdan State)

== "Genes for Breakfast" ==

([[Yixian Song]]) - I've once read a paper of Redfield(1993) "Genes for Breakfast: The Have-Your-Cake and-Eat-lt-Too of '''Bacterial Transformation'''". Though it's an old publication, I still find the idea very inspiring. Well, considering bacteria living in a gene-pool with abandoned DNA strands, each bacterium can randomly "eat" free DNA strands, and use them as nutrition or for DNA repairing or even gene improvement. But the DNA strands were abandoned for a reason. Some of them can be virulent.(!!!) Besides bacteria can exchange DNA with each other, of course. We can define a population size of bacteria, amount of free DNA strands in gene-pool, percentage of virulent DNA and their virulence (impact on the bacteria fitness). We certainly can also consider the bacteria as a metapopulation.("A metapopulation consists of a group of spatially separated populations of the same species which interact at some level." - says wikipedia.org) The question to be answered will be "in which situation the bacterial population will become extinct in the end".

* Cool topic! I'd be happy to brain storm a bit on this ([[Felix Hol]])
* So will I ([[Borys Wrobel]])
* [[Chaitanya Gokhale]]
* [[Oana Carja]]
* [[Ana Hocevar]]

== Patterns in Cenozoic Western US volcanism ==

(Leif Karlstrom) - Allen Glazner (UNC) has put together a neat database of volcanic activity over the past 65 million years in the Western US (here's a [http://rocks.geosci.unc.edu/files/faculty/glazner/Movies/WUS2.mov movie] of it), including location, duration of activity and lava composition. This data is derived from several careers worth of geologic mapping and dating volcanic rocks exposed all over the West. While it is not complete (not everything is preserved, and not everything has been mapped yet), there is a wealth of information about volcanic processes in here. I think it would be neat to mine this dataset for correlations, then think about ways to model it. This could include actual physics and geology, but could also be based solely on the data.

Here is a [http://www.navdat.org/NavdatCoverages/index.cfm link] to data files for this project. More soon.

== Pitch diffusion in groups of musicians ==

(Leif Karlstrom) - When the violin section of an orchestra tunes, the concertmaster gets up and plays a note that all the rest of the violins try to match. I did some experiments in my undergrad with John Toner (physics, U Oregon) where we looked at what happens when the frequency of this tuning note shifts during the time when players are actively trying to match one another. We found that the shifted pitch diffuses through group if it is a small shift (a few Hz), but is immediately sensed by the whole group if it is a large shift. This implies that there is a shift from local to long-range interaction that governs how pitch matching occurs. We envisioned a process similar to flocking behavior in birds for the local interactions, which is governed by an advection-diffusion equation. But we were unable to model the data with this model, because it does not allow for long-range interactions. I still have the data, and would be interested in thinking again about how people process sound in groups.

* Sounds like a cool topic! A quick question: do you have data on the social structure of the orchestra? It would be interesting to look at the formal hierarchy, as well as at the informal social network, and see if it has any influence on pitch diffusion, especially for the long-range interactions. (Question asked by [[Bogdan State]])

* This is interesting and (vaguely) related to an ABM project that a student of mine started some years ago: constructing an ABM that would simulate Pauline Oliveros's "Tuning Meditation." The basic format of this is a large room of participants who choose a "pleasing" tone and sing it for an indeterminate time ("a breath"). They then choose someone else in the crowd and try to match their tone. Iterate. In performances, there is usually convergence to a given tone and duration. Here is a link to one simulation of this:
http://www.actlab.utexas.edu/~mcarroll/tuning.html

It would be fun to do this and try to take into account geometry of the performance space, range of sight, ability to match a tone, etc. (Rockmore)

== Language Evolution in an Archipelago ==

(Erika Fille Legara) - The Philippines is an archipelago containing 7,106 islands with three broader divisions (three main islands): Luzon, Visayas, and Mindanao. It has around 175 individual languages, four of which already have no more known speakers. Moreover, the Constitution recognizes eight (8) major and twelve (12) regional languages (statistics are taken from Wikipedia on the Philippines). It is also interesting to note that most Filipinos know at least three languages: (1) his/her native language, (2) Filipino, and (3) English. Now, if I could get data on the different language distributions (per year or per decade) within the archipelago, it might give us new insights on how certain languages evolve. It would also be interesting to model or predict which languages would eventually thrive and die. Also, I'd like to predict what would happen to certain languages at certain regional boundaries after a few decades or a few centuries. And finally, taking a hint from Professor Dan's idea (above), it may also be interesting to look at how certain words in the Filipino dictionary evolve through time. Caveat: I still need to check if we could have the data available before June.

== ''Social Cognition: Defining the Situation'' ==

(Lynette Shaw) – A foundational concept in social cognition is that of the “mental representation.” Essentially, this is a preexisting framework of meaning that is automatically imposed on perceived information in order to develop the inferences necessary for generating interpretations and expectations from that information. This basic concept bears a strong relationship to many popular ideas in the social sciences such as the “categories” involved in discrimination, cultural “schemas,” the “frames” of social movements, organizational “scripts,” and the “mental models” that are associated with institutions.

In his foundational piece, “On Perceptual Readiness,” Bruner proposes a very simple model of how these representations are essentially “selected for” on the basis of inference validation. Since that time, the complex interdependencies of this automatic, cognitive process occurring within a ''social'' context have been explicitly noted in work dealing with “expectancy confirmation.” Implicitly, the interdependent nature of this process within the social context has arguably undergirded several bodies of both classical and contemporary social theory - especially those relying on an idea of individuals reaching a “shared definition of the situation.”

Though this inference-validation model of mental representation is a relatively simple one, little work to date has really sought to represent it in ways that could be formally or systematically elaborated upon. This project would translate this conceptual model into an agent-based computer simulation and, if time allows, begin exploring key parameterizations of it that have interesting real world analogs.

* If I understand this correctly, I find it interesting :-) [[User:Ligtvoet|Ligtvoet]] 21:37, 21 May 2010 (UTC)
* Thanks! I look forward to getting to talk about it more in person. It's a pretty intuitive concept, but there isn't a lot of established vocabulary for it as of yet. [[Lynette Shaw]]

== "Structure, Function and Spaces" ==

(Giovanni Petri): recently networks have been studied in relation to their space embeddings (usually hyperbolic) for a number of reasons, for example efficient navigation, data filtering or visualization (see [http://arxiv.org/abs/0805.1266 here], [http://arxiv.org/abs/0903.2584 here] and [http://arxiv.org/pdf/0906.4826v1 here]). To wet your appetite, one of the fascinating results is that any graph can be embedded as a planar graph on a surface with sufficiently high genus (i.e. how many donut's hole you make in the space). Now I would be interested in studying whether such hidden metric space analogy goes a bit deeper. For example, whether there is a relation between diffusion and transport properties on a networks and its space embedding, whether interacting systems (think of correlation matrices, multi-body systems etc) can be cast in such form and some of their properties derived from the embedding space's characteristics (say genus, curvature etc etc). As I'm currently reading on the subject but don't have a precise idea how to implement it, I would very much like feedback from any interested peer/p.

== "Ego'o'war" ==

(Giovanni Petri): [http://www.asna.ch/papers/ASNA09_papers_part1_pdf/Brandes-et-al1_paper.pdf Brandes et al.] (link broken) -> [http://www.inf.uni-konstanz.de/algo/publications/lmlbam-lapn-09.pdf This seems to work] recently extracted role-models for ego-networks from a dataset obtained through questionnaire in a large community of immigrants. It would be interesting to use some of the available data to try and identify behavioral archetypes (socialites, noobs, PKers, carebears, griefers etc etc) in online communities, how their interact and evolve. I'm thinking of virtual worlds (as [http://www.eveonline.com Eve Online] or [[Michael Szell]]'s world for instance) as they do present a wider range of possible interactions than standard social networks, i.e. grouping, migrations, wars, commerce etc etc . This project however sounds pretty data-intensive and it might not be easy to get all the data involved.

* ([[Michael Szell]]) I have begun working on exactly this topic, in succession to [http://arxiv.org/abs/1003.5137 this paper]. See [http://www.youtube.com/user/complexsystemsvienna#p/a/u/0/NC-Gtu2yaCU Video of an aggressive player]. One could follow the evolution of some players and their activities in time, and see how their "careers" evolve. I am sure one could observe a lot of interesting things, e.g. "bursty" behavior, long-range correlations, non-gaussian distributions of activity... I can try to extract data from some players, so we can take a look at it in June.

* ([[Giovanni Petri]]) Great! Another issue might be the mobility of virtual agents as opposed to real agents (say from mobile networks). It would be interesting to see if there are any similarities or not (what I'm thinking of is something along the lines of, can we learn something useful for real-world applications from the virtual ones?) and maybe there might be links to the project proposed by [[Bogdan State]] at the top of the page.

* ([[Lynette Shaw]]) There are many aspects of these papers and potential project that might intersect with social-structure based notions of “identity” ([http://www.scribd.com/doc/16210252/Stryker-Identity-Theory good article on the subject]).One line of inquiry has centered on multiple identities (which are connected to the different roles people are expected to play as a result of the different groups to which they belong). Being able to suss out how much career paths depend on histories of involvement with different groups(as opposed to changes in individual traits) might be one way to get at that. In terms of “archetypes,” there also has been a recent drive to look at identity as a “schema” that is picked up in a social context and then imposed upon one’s own self. Once this happens, this “schema” then determines an individual’s social behavior. I would be interested in seeing if there was a way here to capture how well an individual’s exposure to certain models of behavior predicts their own subsequent behavior patterns.

== Development of an online environment for simple behavioral experiments ==

([[Michael Szell]]): Classic "bottom-up" behavioral experiments, such as conducted by [http://www.santafe.edu/~bowles/2005_BBS.pdf Henrich et al.] or [http://www.pnas.org/content/107/7/2962.full Traulsen et al.] [http://www.pnas.org/content/107/12/5265.full ..Meta-Info], face three main problems:
#) It is highly cumbersome and resource-intensive to set up a physical environment, and to assemble enough subjects who take part in your experiments (usually they have to be paid)
#) The subjects are often students or another possibly non-representative/biased sample of the human population
#) It is not possible to assemble more than a few dozen/hundreds of subjects, leading to possibly non-significant results. Number of subjects scales linearly with cost.

It is baffling how scientists (with very few exceptions) have so far avoided the vastness of the internet population for conducting such behavioral experiments. Problem 1) can be solved with a relatively small amount of resources, by setting up an online environment for experiments. Problem 2) shifts, as the bias shifts (depending on the subjects you attract). However, problem 3) is solved instantly, as >10^4 subjects which you can easily motivate over time (with practically zero running cost) will guarantee statistical significance. My proposal is to gather experts in software engineering / web development / experimental setup, to develop such an online environment (as simple as possible). I suggest it should be [http://en.wikipedia.org/wiki/Ajax_%28programming%29 AJAX]+[http://en.wikipedia.org/wiki/LAMP_%28software_bundle%29 LAMP]-based, portable, open-source, and as easy as possible to embed on any page having MySQL/PHP behind. This way it could serve its experiments as "mini-games" in e.g. bigger browser-games, or on other sites. The first implemented experiment could be the [http://en.wikipedia.org/wiki/Ultimatum_game Ultimatum game]. Note that I have no experience with AJAX, so this project would need someone qualified in this field.

== "Phenotypic Plasticity and Climate Change" ==

(Kyla Dahlin): One of the biggest challenges to understanding how ecosystems will change with a changing climate is that we don't know species' fundamental niches. People like to take existing distributions ("realized niches"), correlate them with climate, then project where that climate will move in the future, but that ignores the fact that plants could actually be able to tolerate a much wider range of conditions than those we currently find them in. It sees like you could get a better handle on this if you knew (1) a plant's generation time, (2) how many generations it takes to evolve a new trait, and (3) the climate the plant experienced in the past. If the timescale of a plant's evolution is similar to that of, say, glacial cycles, that would suggest that the plant could handle a pretty wide range of temperatures and weather extremes. I'd love to know if any of the evolutionary bio folks have thought about this or know the literature better than I do!

== Quantitative Analysis of Northern New Mexico Acequia Infrastructure: An Applied Complexity Approach ==

([[John Paul]])

New Mexico has community ditch irrigation systems called [http://en.wikipedia.org/wiki/Acequia acequias] that are some of the oldest decentralized European social structures in the Americas. Some [http://dlc.dlib.indiana.edu/dlc/bitstream/handle/10535/5637/Cox%20dissertation.pdf?sequence=1 work] has been done by a [http://www.indiana.edu/~spea/prospective_students/doctoral/job_placement/cox_michael.shtml previous CSSS student] studying the social structure of acequias and how they are both sustainable and vulnerable to novel disturbances. More academic work can be found [http://www.kcl.ac.uk/content/1/c6/04/70/19/WithnallDissertation.pdf here] discussing social structures. Most of this work has been qualitative traditional sociological work.

I've come across some data from the New Mexico Office of the State Engineer detailing acequia water rights infrastructure I think may be interesting to look at. Please see the spreadsheets on [http://www.nmacequiacommission.state.nm.us/acequia-list.html this page].

Cursory data analysis is a good place to start.

I'm eventually interested either crafting a model to simulate acequia network growth (theoretical) for historical research purposes, or some research into the statewide structure of acequias that may determine future policy recommendations (applied).

-== emergence and decay of common property management regimes. ==

Inspired by [http://en.wikipedia.org/wiki/Elinor_Ostrom Ostrom]'s work into common property regimes, I've been interested in Agent-based-simulations of these institutions, and how they are created and destroyed. There are a few readings around that [http://www.citeulike.org/user/livingthingdan/tag/santafe here] - including Cox's thesis from John Paul's link list.

--- [[User:Dan90|Dan MacKinlay]]

== "Roadkill as a means of spreading disease in Tasmanian Devils" ==

([[Gavin Fay]]) - Living in Tasmania, it is hard not to become familiar with the plight of the Tasmanian Devil, whose population is currently dwindling due to Devil Facial Tumour Disease (DFTD), a rather nasty infectious cancer which has become prevalent through much of the state. DFTD infection relies on transmission of infected cells from contact, most likely due to biting, which these critters do a lot of during mating and around prey carcasses. A hot conservation topic right now is forestry plans to build roads opening up a wilderness area in the north of the state to ecotourism opportunities. The devil population in this area has until now remained disease free.
There are concerns that the road will increase the likelihood that DFTD will spread to the diseasse-free population: Devils are scavengers and frequently feed on roadkill, the creation of a road may then provide an opportunity for increased frequency of contact between infected and disease-free devils. It might be interesting to investigate how introducing a fixed-location source of additional prey items (ie a road) to a devil population would change the contact network for Devils, and then also to what extent the increased contact frequency would have to be to facilitate transmission of DFTD from an infected devil population to a disease-free one.

* This sounds interesting, especially if you have some data on how the populations move/interact/etc? I've done some predator/prey dynamic modeling both as ODE and Cellular Automata (CA), and I'd suspect CA would be an interesting approach. We should talk! ([[Megan Olsen]])

** I really like this project, specially if you taeckle it from a CA approach...this is a technique I would like to understand better!! I am a biologist, and have been working with diseases spread in spatial structures (malaria), but from differential equations modelling and time series...I would really like to be part of this project if it turns out to become one! Please, let me know! (Vanessa Weinberger)

* Moving this to it's own page, [[Devils and Roadkill]]. ([[Gavin Fay]])

== "Manage lots of fish stocks, or a few?" ==

([[Gavin Fay]]) - Australia's Southern and Eastern Scalefish and Shark Fishery (SESSF) is a multiple species fishery with a large number of vessels operating using a range of gears. The fishery exploits 80+ species, with a subset of target species managed by a total allowable catch (TAC) under a quota management system. Management of other species within the fishery is controlled by other measures such as trip limits, gesar restrictions, and spatial and seasonal closures. Specification of TACs requires data collection and routine stock assessment in order to calculate suitable catch limits given an assessment of stock status.

It is not feasible to perform full quantitative analyses for each quota species on an annual basis (from both a data perspective, instituional capacity, $$$, and other reasons) and rapid assessment methods are prevalent (or absent).
Given that the fishery is multiple species there exist a considerable number of technical interactions within the fishery. ie targeting one species leads to catch of several others - single fishing opportunities (shots, hauls) are not single species.

Given these interactions: Which species should we manage for? Are there a suite of species that we can actively manage for such that the risk to other stocks is not too great? Should we target the high-value species, abundant species (that may be low in value per kg but overall count big $), or manage to minimise the catch of vulnerable species? What are the effects of these options on ecosystem biomass, proportion of stocks in danger of collapse, yield, profit, etc?

Indeed, just describing the multispecies interactions (which species are associated with others in the data, how do these fishery assemblages vary over time and space (perhaps by port)), would be an exercise in itself. Perhaps one could also look at the relative costs to a port-based community associated with the fished assemblage shifting from one to another (perhaps as a result of climate change?).

* ([[Chaitanya Gokhale]]) If I understand the idea correctly I think this can be dealt with an evolutionary game theoretic approach. Although not completely, as per the reasons you have already stated, maybe we can abstract the system out to some important interactions for e.g. targeted catch of one species drags along some other species with it. I don't know if this makes sense, we can discuss it further next week.

== "Estimating abundance trends of non-target species" ==

([[Gavin Fay]]) - Trends in abundance of non-target, or bycatch species in fisheries is generally achieved by the results of fishery independent surveys. Surveys are expensive, and are not always available. How then can we estimate trends when these data are not available? Direct effects (ie incidental harvesting) can be measured (time series of catch), and it might be expected that the relative trends in exploitation rate of bycatch species should be similar to those target species with which the bycatch species are taken. This idea has been attempted in multispecies assessments under a 'Robin Hood' approach (steal from the data-rich to give to the poor). An issue is that the lack of information for the data-poor species can degrade the performance of the data-rich assessment, when the assessments are conducted simultaneously in a multispecies framework.

I'm thinking about a general multivariate state-space modelling framework for nontarget species, which could use correlations of direct effects with target species derived from fisheries logbook data, and the 'known' abundances and trends of the target species.
An additional question is how to quantify indirect effects of fishing on abundance of nontarget species. One possibility could be to guide the covariance with the results of foodweb modelling, which could be limited to simply describing how connected nontarget species are with the various target species. Another might be to use information about life history, or trophic level to describe general expectations for the degree of correlation/change.
It might be useful to make use of a system where it is possible to groundtruth methods - ie an ecosystem for which survey data are available. Alternatively, one could subset the data-rich species.

== "Evolution of life history strategies in sea lions" ==

([[Gavin Fay]]) - The Australian sea lion (ASL) is unique among the otariids (fur seals and sea lions) in that it exhibits a non-annual breeding strategy, with breeding cycle of ~17 months, an extended pupping season at rookeries of 4-5 months, and non-synchronous pupping among subpopulations (rookeries). In contrast, all other sea lions breed on 12 monthly cycle, with short pupping seasons, for which most species is synchronised among rookeries for the entire population.

A proposed idea is that the ASL strategy is in response to living in a low productivity environment (most other fur seals and sea lions live in highly productive, nutrient rich places). with the ability to vary the delay in implantantion of fertilised eggs depending on environmental conditions, thus enabling indiviudals to only invest in reproductive output when the probability for pup survival is high. Indeed, there is evidence that the length of breeding period is correlated with environemntal conditions.
Perhaps it would be neat to see whether the 2 different life history strategies observed are concordant with the hypotheses given evolutionary pressure. I am not familiar with the methods involved, but one could evolve a suite of life histories given different environmental regimes and see which survive?

== "How do organisms use space?" ==

([[Andrew Hein]]). One fundamental problem in ecology and evolution is determining how and why organisms use space in the ways they do. Different organisms experience their environments at different “characteristic” spatial scales. For example, without the aid of technology, humans perceive and interact with their environments on the scale of meters (by sight) to kilometers (by sound or by walking from one place to another). Other organisms like bacteria perceive and interact with their environments on much smaller scales (e.g. micrometers). What determines these scales? Is it possible to predict the characteristic scale of an organism by knowing something about that organism? How do characteristic scales evolve and are they evolutionarily plastic or robust?

I envision two possible approaches to this problem. The first might be an evolutionary approach that assumes that characteristic scales evolve as a result of the need for organisms to communicate with one another. This would involve developing some evolutionary rules and allowing a network of organisms to “evolve” via simulations. These simulations could be used to understand the evolution and plasticity of characteristic scales. The second approach would be to try to understand what factors constrain the spatial scales used by different types of organisms. This might involve building some biological/physical models to try to predict how spatial scales ought to vary among organisms. These models could be compared to a data set on the spatial scales used by a broad variety of animals (I have one such data set).

* ([[Giovanni Petri]]) Sounds pretty cool if I get it right. Also, I'm interested in information spreading myself, this looks very relevant for other applications, e.g. couple information/transportation systems.
* ([[Megan Olsen]]) I'm also interested in the use of space, especially in ecology. I could see using genetic networks as a way to evolve the rules.
* ([[Kyla Dahlin]]) Thinking about the memory/ cognition part of how animals use space, there's some work using brain/body size ratios as a proxy for intelligence (some of this work is shady, but at least the data exists) which might be an interesting addition to a predictive model of spatial scales.
== "Does H1N1 make a comeback?" ==

(Xin Wang). In the last half year of 2009 and at the beginning of 2010, H1N1 diseases swept the whole world including China. At that time the TV programs were all filled with such related news. Somebody said that it was the conspiracy, but whether or not it is true, we have to focus on what we should do to prevent some unknown disease from being pandemic because the sweeping of another unkown disease all over the world will occur sooner or later such as H5N1 and SARS in 2003. So analyzing the evolution of the virus from the molecular level combining with the spread of the disease in the population from the macro level may help us find the general way to prevent the concept virus from outbreaking.

Traditionally we use SIR, SEIR and etc. to model the spread of the disease. Here we may use the multi-agent-based method to model the virus including genes and protein, and human beings, and to simulate three processes, the first of the evolution of the virus, the second of interaction between human and virus, the third of the infection with people moving. Because of my background in mathematical control theory and game theory, not in molecule biology or ecology, I am short of knowledge on biology and I am not sure whether or not this idea is feasible. Maybe make some restriction from the biological view is necessary.

== Adding Genetics to Community phase-synchronization ==

(Vane Weinberger)- Browsing through Spatial Food Webs literature, I ran into a paper that I loved since the minute I read it: although a little too old, Blasius and Stone (1999)[[http://www.lifesciences.tau.ac.il/departments/zoology/members/stone/documents/Chaosandphasesynchr...pdf]] simulated a simple tri-trophic ecological system that was able of the most incredibles fluctuations! I believe that this system can be expanded (maybe adding other relations into the local throphics phenomena), but what I REALLY wanted to add into the model was the population genetic subject: this work demostrate the great ammount of population crashes that are seen in a patch system and how they can be recovered when submerged on a spatial migrating system. However, as they are modelling the system from bottom-up approaches and thus adding the population-level processes of each guild, we could ask about how bad can these crashes affect the survival of the guild if we consider an Allee Effect or inbreeding phenomena. I do not know if someone has already done this before, but I think that this model would help us understand more about conservations efforts in the wild.

*([[Andrew Hein]]) This is a really nice idea. It would be interesting to try to track local and global oscillations in population genetic structure in the system you describe. It would also be interesting to try to determine the degree to which oscillations in genetic structure are synchronized (or out of phase) with population oscillations.

== Scale-Free Networks in intertidal communities ==

Network Topology effects on population structure (Vane Weinberger)- In 2005, Nowak's team demostrated that certain networks topologies could alter the random fixation of an allelle (simulated through the Moran Process). More precisely, they discovered networks with many hubs augmented the effect of natural selection. The intertidal system is known for its great ammount of sessile or limited dispersal animals that can only disperse through their larval stage. Therefore, it was believed that the genetic population structure of a population was mainly a function of their dispersal capabilities (as larvae). However, if there is a sexual-limited-contact of their progenitors, which could create a network topology with many hubs (it happens in some gastropods) it could happen that there is an effect of the network topology that could alter the genetic population despite the homogeneization of the larvae pool. (Notice the two different contact networks that are created though this simulation...that something that is also worth for studyin, I am sure this could happen in other systems!). I apologize: this idea was discussed a long time ago and I stopped browsing about how to taeckle the topic...but I am sure we could arrange something for this!

*([[Roberta Sinatra]]) I would be very interested. Actually I am working on a dynamical model to detect topological communities on graphs, ispired to how genotype of walkers mutate when they move on the graph, meet and interact. Although I am more interested in finding topological properties of the graphs, I think that a realistic model based on plausible biological and genetic assumptions can highlight interesting properties of some self-organized systems. We can have a chat about that!

== Modeling evolutionary dynamics of spatially structured populations ==

([[Felix Hol]]) -- I am very interested in the interplay between ecology and evolution. Motivated by Sewall Wright's seminal 1932 [http://www.blackwellpublishing.com/ridley/classictexts/wright.pdf paper] I would like to investigate the effect that metapopulation formation has on the speed of evolution. The computational model to investigate this could be based on work by Mitchell & Crutchfield (and coworkers) where a genetic algorithm evolves a population of cellular automata to perform a certain task (see this [http://www.pnas.org/content/92/23/10742.full.pdf paper]).
I propose to embed population structure in the genetic algorithm (GA) and find out what effect this has on the capabilities of the GA. One way of doing this might be to (bluntly) define subpopulations that cross breed at specified intervals; but I am sure that there are much more elegant/sophisticated ways of embedding structure. Some (wild) ideas for this are: putting them on graphs or lattices (with or without vacancies/movement)…. Any suggestions are greatly appreciated! (also other ideas for modeling stuff like this (evolutionary game theory etc..) are welcome)

* I have the same idea and I am thinking about how to train the initial structure to be the one robust to different situations. (Xin Wang)
* What about a metapopulation approach on a cellular automata? Each cell is a metapopulation, therefore giving local rules for the metapopulation and then global rules for the entire population (including migration). ([[Megan Olsen]])
* I was considering introducing population structure in my artificial evolution system (which uses a GA now). It is not based on cellular automata but on artificial gene regulatory networks. ([[Borys Wrobel]])
* ([[Andrew Hein]]) I have some ideas based on metapopulation and metacommunity models that may be pertinent. Sounds like a cool problem.
* lets meet to chat about this project tonight (tuesday 8/6) at 8:30
* some relevant papers are: [http://www.pnas.org/content/99/16/10516.abstract] and [http://www-binf.bio.uu.nl/pdf/Pagie.cec00.pdf]

== The self-generation of patterns in Five-in-Row Game ==

(Xin Wang). In any human-machine or machine-machine game for chess, go, Five-in-Row and etc., the choice of patterns is very important, and so a good game-playing computer is always trained by both computer scientists and professional human players. After patterns are fixed, the weight of each pattern in the evaluation function can be optimized by NN, GA and other optimization methods. Although the depth of searching is another important factor, it only depends on fast searching algorithms and pruning algorithms. So the study on patterns makes sense to complex system. Traditionally the patterns are always fixed but here my initial idea is to train the computer to self generate its own patterns for use. This idea is very similar to "work by Mitchell & Crutchfield (and coworkers) where a genetic algorithm evolves a population of cellular automata to perform a certain task (see this [http://www.pnas.org/content/92/23/10742.full.pdf paper])." (see above part by Felix Hol).

== '''Network's shortest paths''' ==

([[Sergey Melnik]])

Consider a random network consisting of ''N'' nodes where each pair of nodes is connected with a given probability ''p'' ([http://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model see Erdos-Renyi random graph]). The question is about the shortest path through the network from one node to another (also called geodesic path, or intervertex distance):

Can we calculate analytically (and exactly) the probability distribution of shortest paths in such a network? That is, how likely it is that a pair of nodes chosen at random will be distance ''D'' apart. For distance ''D''=1 the answer is obviously ''p''. What are such probabilities for distances ''D''=2, ''D''=3, ''D''=4, etc.?

Note that the network has a finite number of nodes (which is not necessarily large) and there are only 2 parameters here, ''N'' and ''p''.
This is a simple yet fundamental question and there is much more to follow in terms of immediate applications and new theories once we answer it.

== '''The Monopoly project''' ==

([[Sergey Melnik]])

Have you ever wondered about the best strategy to play [http://en.wikipedia.org/wiki/Monopoly_%28game%29 Monopoly]?

We can start by answering simple questions such as "is it really better to be the first to throw the dice?", or "what are the most valuable squares on the field, and when?", or "to what extent do your skills help you overcome randomness to win this game?", or "how long would a game last?", or "how does all this changes with the number of players?". We can then go deeper to model negotiations and resource management strategies - plenty of possibilities here.

I am sure those who play this game already have some intuition. But can we precisely quantify these and other effects? I guess not yet. I think there is a lot here that can be modelled (analytically?) and compared with numerical (Monte Carlo?) simulations.

Finally, we can look into creating a new, even more exciting game to be played by the future generations. And surely you will have ''better calculated'' chances next time you play Monopoly with your friends!

* I don't have references, but a friend of mine, who plays Monopoly competitions, has a whole bunch of rules that lead to better outcomes: what streets to buy, what streets not to buy etc. So to a certain extent somebody has done something familiar [[User:Ligtvoet|Ligtvoet]]

== Properties of evolving artificial gene regulatory networks ==

see [[Properties of evolving artificial gene regulatory networks]] ([[Borys Wrobel]])

I have built an artificial life platform (right now, it uses a genetic algorithm) that can generate a large number of gene regulatory networks that have evolved to perform certain computations (for example, process signals). I would be interested in investigating what are the statistical (or other) properties of these networks.

Here is a paper that describes (a version) of the [http://www.alifexi.org/papers/ALIFExi_pp297-304.pdf model].

== '''Grouping behavior and the evolution of animal migration''' ==

[[Andrew Hein]]

This project will start with some of the grouping behavior models that Ian Couzin showed us (see an example [[http://webscript.princeton.edu/~icouzin/website/wp-content/uploads/2010/05/couzin05.pdf]]). In addition to individuals evolving the ability to be 'informed' about the migratory route, I'd like to add another evolutionary trait: the ability to store fuel (e.g. fat). Increasing the amount of fuel stored is like increasing the amount of gas you put in your car. If you have some imperfect information about where you want to go, you are more likely to eventually get there without running out of gas if you start with more gas. In the case of migratory animals, increased fuel storage allows animals to search the landscape for a longer period of time. However, fuel storage comes at a great cost--individuals that store a lot of fuel experience drastically increased drag (fish, birds) and they must spend a lot of time gathering fuel before they migrate.

The goal of this project would be to let individuals evolve BOTH the ability to store information about the migratory route at a cost as in Ian's models, and the ability to store more fuel at a cost. I'd like to see what types of trait combinations evolve over a number of generations. Let me know if you're interested.

* I'm not familiar with the topic and I guess I lack some knowledge on this, but I find it very interesting and would like to learn more and contribute in some way. ([[Ana Hocevar]])

== '''The blogosphere as a complex network: an empirical laboratory''' ==

[[Massimiliano Spaziani]]

Blognation (http://www.blognation.it) is an aggregator of the Italian blogosphere.
2.500 blogs are aggregated, each blog produces about 10 posts a day, and a semantic engine automatically extracts tags (concepts) for each post.
The database of the aggregator contains information about the relationships between blog and blog, and between post and concepts. Timestamp is traced.
The database (MySQl) of the blog aggregator may be used as a laboratory where empirically measure network properties, calculate hubs and authorities, and design algorithms for post and blog ranking, for determining trends in time, etc.

* [[Kang Zhao]] I am interested in this project.

Sergey Melnik

2010-06-08T23:52:26Z

Sergey:

[[Image:Svm.jpg|thumb|left|200px|Sergey Melnik]]
Here is a link to my homepage:
http://www.ul.ie/sdcs/sergey

==Projects in mind==

'''Network's shortest paths'''

Consider a random network consisting of ''N'' nodes where each pair of nodes is connected with a given probability ''p'' ([http://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model see Erdos-Renyi random graph]). The question is about the shortest path through the network from one node to another (also called geodesic path, or intervertex distance):

Can we calculate analytically (and exactly) the probability distribution of shortest paths in such a network? That is, how likely it is that a pair of nodes chosen at random will be distance ''D'' apart. For distance ''D''=1 the answer is obviously ''p''. What are such probabilities for distances ''D''=2, ''D''=3, ''D''=4, etc.?

Note that the network has a finite number of nodes (which is not necessarily large) and there are only 2 parameters here, ''N'' and ''p''.
This is a simple yet fundamental question and there is much more to follow in terms of immediate applications and new theories once we answer it.

--------
'''The Monopoly project'''

Have you ever wondered about the best strategy to play [http://en.wikipedia.org/wiki/Monopoly_%28game%29 Monopoly]?

We can start by answering simple questions such as "is it really better to be the first to throw the dice?", or "what are the most valuable squares on the field, and when?", or "to what extent do your skills help you overcome randomness to win this game?", or "how long would a game last?", or "how does all this changes with the number of players?". We can then go deeper to model negotiations and resource management strategies - plenty of possibilities here.

I am sure those who play this game already have some intuition. But can we precisely quantify these and other effects? I guess not yet. I think there is a lot here that can be modelled (analytically?) and compared with numerical (Monte Carlo?) simulations.

Finally, we can look into creating a new, even more exciting game to be played by the future generations. And surely you will have ''better calculated'' chances next time you play Monopoly with your friends!

Sergey Melnik

2010-06-07T06:36:10Z

Sergey:

[[Image:Svm.jpg|thumb|left|200px|Sergey Melnik]]
Here is a link to my homepage:
http://www.ul.ie/sdcs/sergey

File:Svm.jpg

2010-06-07T06:29:10Z

Sergey:

CSSS 2010 Santa Fe-Projects & Working Groups

2010-06-07T06:15:07Z

Sergey:

{{CSSS 2010 Santa Fe}}

Students are required to craft a research project -- use this page to brainstorm and organize your efforts.

Evolution of Words (Dan Rockmore) - In a class on complex systems that I teach at Dartmouth one of the final projects seemed to indicate from a small and somewhat biased sample of English words, that word origins (as indicated by one of the online dictionaries) seem clustered at certain times. As a start I would propose a mining of this info in some online dictionary, performing some initial analysis and see if "there is a there, there.." and if so, keep on going.

----------

Dynamics of Equities Market Structure (Dan Rockmore) -- In a paper of mine w/some of my buddies (some of whom you will meet this summer), "Topological Structures in the Equities Market," PNAS December 30, 2008 vol. 105 no. 52 20589-20594, we found some interesting structure in the correlation network of the NYSE equities market. This required a choice of a time window. It would be interesting to see how/if this structure changes over time and window size, especially on either side of market crises. Scott Pauls has code that could be used to do some of this analysis.

----------

Style of Chess Play (Dan Rockmore) -- I am curious to see if using tools from learning one can characterize the "style" of a chess player. The website www.playchess.com has a database of chess games. I'm not sure if the annotation would enable the determination of particular players, but even without that, can clustering on the move data give sensible/interesting results with respect to style of play?

-----------

Movement Careers of Couchsurfing.org members (Bogdan State) - I am working with Couchsurfing.org and two Stanford Professors in trying to analyze this social movement organization's member data. One aspect both we and the Couchsurfing management are interested in is the evolution of members in the movement over time. I would like to perform a preliminary analysis of these "movement careers", using a sample of about 10,000 nodes (out of 1.7 milion) we are scheduled to obtain soon.

----------

"Genes for Breakfast" (Yixian Song) - I've once read a paper of Redfield(1993) "Genes for Breakfast: The Have-Your-Cake and-Eat-lt-Too of '''Bacterial Transformation'''". Though it's an old publication, I still find the idea very inspiring. Well, considering bacteria living in a gene-pool with abandoned DNA strands, each bacterium can randomly "eat" free DNA strands, and use them as nutrition or for DNA repairing or even gene improvement. But the DNA strands were abandoned for a reason. Some of them can be virulent.(!!!) Besides bacteria can exchange DNA with each other, of course. We can define a population size of bacteria, amount of free DNA strands in gene-pool, percentage of virulent DNA and their virulence (impact on the bacteria fitness). We certainly can also consider the bacteria as a metapopulation.("A metapopulation consists of a group of spatially separated populations of the same species which interact at some level." - says wikipedia.org) The question to be answered will be "in which situation the bacterial population will become extinct in the end".

* Cool topic! I'd be happy to brain storm a bit on this (Felix Hol)

----------

Patterns in Cenozoic Western US volcanism (Leif Karlstrom) - Allen Glazner (UNC) has put together a neat database of volcanic activity over the past 65 million years in the Western US (here's a [http://rocks.geosci.unc.edu/files/faculty/glazner/Movies/WUS2.mov movie] of it), including location, duration of activity and lava composition. This data is derived from several careers worth of geologic mapping and dating volcanic rocks exposed all over the West. While it is not complete (not everything is preserved, and not everything has been mapped yet), there is a wealth of information about volcanic processes in here. I think it would be neat to mine this dataset for correlations, then think about ways to model it. This could include actual physics and geology, but could also be based solely on the data.

----------

Pitch diffusion in groups of musicians (Leif Karlstrom) - When the violin section of an orchestra tunes, the concertmaster gets up and plays a note that all the rest of the violins try to match. I did some experiments in my undergrad with John Toner (physics, U Oregon) where we looked at what happens when the frequency of this tuning note shifts during the time when players are actively trying to match one another. We found that the shifted pitch diffuses through group if it is a small shift (a few Hz), but is immediately sensed by the whole group if it is a large shift. This implies that there is a shift from local to long-range interaction that governs how pitch matching occurs. We envisioned a process similar to flocking behavior in birds for the local interactions, which is governed by an advection-diffusion equation. But we were unable to model the data with this model, because it does not allow for long-range interactions. I still have the data, and would be interested in thinking again about how people process sound in groups.

* Sounds like a cool topic! A quick question: do you have data on the social structure of the orchestra? It would be interesting to look at the formal hierarchy, as well as at the informal social network, and see if it has any influence on pitch diffusion, especially for the long-range interactions. (Question asked by [[Bogdan State]])

* This is interesting and (vaguely) related to an ABM project that a student of mine started some years ago: constructing an ABM that would simulate Pauline Oliveros's "Tuning Meditation." The basic format of this is a large room of participants who choose a "pleasing" tone and sing it for an indeterminate time ("a breath"). They then choose someone else in the crowd and try to match their tone. Iterate. In performances, there is usually convergence to a given tone and duration. Here is a link to one simulation of this:
http://www.actlab.utexas.edu/~mcarroll/tuning.html

It would be fun to do this and try to take into account geometry of the performance space, range of sight, ability to match a tone, etc. (Rockmore)
----------

Language Evolution in an Archipelago (Erika Fille Legara) - The Philippines is an archipelago containing 7,106 islands with three broader divisions (three main islands): Luzon, Visayas, and Mindanao. It has around 175 individual languages, four of which already have no more known speakers. Moreover, the Constitution recognizes eight (8) major and twelve (12) regional languages (statistics are taken from Wikipedia on the Philippines). It is also interesting to note that most Filipinos know at least three languages: (1) his/her native language, (2) Filipino, and (3) English. Now, if I could get data on the different language distributions (per year or per decade) within the archipelago, it might give us new insights on how certain languages evolve. It would also be interesting to model or predict which languages would eventually thrive and die. Also, I'd like to predict what would happen to certain languages at certain regional boundaries after a few decades or a few centuries. And finally, taking a hint from Professor Dan's idea (above), it may also be interesting to look at how certain words in the Filipino dictionary evolve through time. Caveat: I still need to check if we could have the data available before June.

----------

''Social Cognition: Defining the Situation'' (Lynette Shaw) – A foundational concept in social cognition is that of the “mental representation.” Essentially, this is a preexisting framework of meaning that is automatically imposed on perceived information in order to develop the inferences necessary for generating interpretations and expectations from that information. This basic concept bears a strong relationship to many popular ideas in the social sciences such as the “categories” involved in discrimination, cultural “schemas,” the “frames” of social movements, organizational “scripts,” and the “mental models” that are associated with institutions.

In his foundational piece, “On Perceptual Readiness,” Bruner proposes a very simple model of how these representations are essentially “selected for” on the basis of inference validation. Since that time, the complex interdependencies of this automatic, cognitive process occurring within a ''social'' context have been explicitly noted in work dealing with “expectancy confirmation.” Implicitly, the interdependent nature of this process within the social context has arguably undergirded several bodies of both classical and contemporary social theory - especially those relying on an idea of individuals reaching a “shared definition of the situation.”

Though this inference-validation model of mental representation is a relatively simple one, little work to date has really sought to represent it in ways that could be formally or systematically elaborated upon. This project would translate this conceptual model into an agent-based computer simulation and, if time allows, begin exploring key parameterizations of it that have interesting real world analogs.

* If I understand this correctly, I find it interesting :-) [[User:Ligtvoet|Ligtvoet]] 21:37, 21 May 2010 (UTC)
* Thanks! I look forward to getting to talk about it more in person. It's a pretty intuitive concept, but there isn't a lot of established vocabulary for it as of yet. [[Lynette Shaw]]

----------

"Structure, Function and Spaces" (Giovanni Petri): recently networks have been studied in relation to their space embeddings (usually hyperbolic) for a number of reasons, for example efficient navigation, data filtering or visualization (see [http://arxiv.org/abs/0805.1266 here], [http://arxiv.org/abs/0903.2584 here] and [http://arxiv.org/pdf/0906.4826v1 here]). To wet your appetite, one of the fascinating results is that any graph can be embedded as a planar graph on a surface with sufficiently high genus (i.e. how many donut's hole you make in the space). Now I would be interested in studying whether such hidden metric space analogy goes a bit deeper. For example, whether there is a relation between diffusion and transport properties on a networks and its space embedding, whether interacting systems (think of correlation matrices, multi-body systems etc) can be cast in such form and some of their properties derived from the embedding space's characteristics (say genus, curvature etc etc). As I'm currently reading on the subject but don't have a precise idea how to implement it, I would very much like feedback from any interested peer/p.

----------

"Ego'o'war" (Giovanni Petri): [http://www.asna.ch/papers/ASNA09_papers_part1_pdf/Brandes-et-al1_paper.pdf Brandes et al.] (link broken) -> [http://www.inf.uni-konstanz.de/algo/publications/lmlbam-lapn-09.pdf This seems to work] recently extracted role-models for ego-networks from a dataset obtained through questionnaire in a large community of immigrants. It would be interesting to use some of the available data to try and identify behavioral archetypes (socialites, noobs, PKers, carebears, griefers etc etc) in online communities, how their interact and evolve. I'm thinking of virtual worlds (as [http://www.eveonline.com Eve Online] or [[Michael Szell]]'s world for instance) as they do present a wider range of possible interactions than standard social networks, i.e. grouping, migrations, wars, commerce etc etc . This project however sounds pretty data-intensive and it might not be easy to get all the data involved.

* ([[Michael Szell]]) I have begun working on exactly this topic, in succession to [http://arxiv.org/abs/1003.5137 this paper]. See [http://www.youtube.com/user/complexsystemsvienna#p/a/u/0/NC-Gtu2yaCU Video of an aggressive player]. One could follow the evolution of some players and their activities in time, and see how their "careers" evolve. I am sure one could observe a lot of interesting things, e.g. "bursty" behavior, long-range correlations, non-gaussian distributions of activity... I can try to extract data from some players, so we can take a look at it in June.

* ([[Giovanni Petri]]) Great! Another issue might be the mobility of virtual agents as opposed to real agents (say from mobile networks). It would be interesting to see if there are any similarities or not (what I'm thinking of is something along the lines of, can we learn something useful for real-world applications from the virtual ones?) and maybe there might be links to the project proposed by [[Bogdan State]] at the top of the page.

* ([[Lynette Shaw]]) There are many aspects of these papers and potential project that might intersect with social-structure based notions of “identity” ([http://www.scribd.com/doc/16210252/Stryker-Identity-Theory good article on the subject]).One line of inquiry has centered on multiple identities (which are connected to the different roles people are expected to play as a result of the different groups to which they belong). Being able to suss out how much career paths depend on histories of involvement with different groups(as opposed to changes in individual traits) might be one way to get at that. In terms of “archetypes,” there also has been a recent drive to look at identity as a “schema” that is picked up in a social context and then imposed upon one’s own self. Once this happens, this “schema” then determines an individual’s social behavior. I would be interested in seeing if there was a way here to capture how well an individual’s exposure to certain models of behavior predicts their own subsequent behavior patterns.

----------

Development of an online environment for simple behavioral experiments ([[Michael Szell]]): Classic "bottom-up" behavioral experiments, such as conducted by [http://www.santafe.edu/~bowles/2005_BBS.pdf Henrich et al.] or [http://www.pnas.org/content/107/7/2962.full Traulsen et al.] [http://www.pnas.org/content/107/12/5265.full ..Meta-Info], face three main problems:
#) It is highly cumbersome and resource-intensive to set up a physical environment, and to assemble enough subjects who take part in your experiments (usually they have to be paid)
#) The subjects are often students or another possibly non-representative/biased sample of the human population
#) It is not possible to assemble more than a few dozen/hundreds of subjects, leading to possibly non-significant results. Number of subjects scales linearly with cost.

It is baffling how scientists (with very few exceptions) have so far avoided the vastness of the internet population for conducting such behavioral experiments. Problem 1) can be solved with a relatively small amount of resources, by setting up an online environment for experiments. Problem 2) shifts, as the bias shifts (depending on the subjects you attract). However, problem 3) is solved instantly, as >10^4 subjects which you can easily motivate over time (with practically zero running cost) will guarantee statistical significance. My proposal is to gather experts in software engineering / web development / experimental setup, to develop such an online environment (as simple as possible). I suggest it should be [http://en.wikipedia.org/wiki/Ajax_%28programming%29 AJAX]+[http://en.wikipedia.org/wiki/LAMP_%28software_bundle%29 LAMP]-based, portable, open-source, and as easy as possible to embed on any page having MySQL/PHP behind. This way it could serve its experiments as "mini-games" in e.g. bigger browser-games, or on other sites. The first implemented experiment could be the [http://en.wikipedia.org/wiki/Ultimatum_game Ultimatum game]. Note that I have no experience with AJAX, so this project would need someone qualified in this field.

----------

"Phenotypic Plasticity and Climate Change" (Kyla Dahlin): One of the biggest challenges to understanding how ecosystems will change with a changing climate is that we don't know species' fundamental niches. People like to take existing distributions ("realized niches"), correlate them with climate, then project where that climate will move in the future, but that ignores the fact that plants could actually be able to tolerate a much wider range of conditions than those we currently find them in. It sees like you could get a better handle on this if you knew (1) a plant's generation time, (2) how many generations it takes to evolve a new trait, and (3) the climate the plant experienced in the past. If the timescale of a plant's evolution is similar to that of, say, glacial cycles, that would suggest that the plant could handle a pretty wide range of temperatures and weather extremes. I'd love to know if any of the evolutionary bio folks have thought about this or know the literature better than I do!

--------

Quantitative Analysis of Northern New Mexico Acequia Infrastructure: An Applied Complexity Approach ([[John Paul]])

New Mexico has community ditch irrigation systems called [http://en.wikipedia.org/wiki/Acequia acequias] that are some of the oldest decentralized European social structures in the Americas. Some [http://dlc.dlib.indiana.edu/dlc/bitstream/handle/10535/5637/Cox%20dissertation.pdf?sequence=1 work] has been done by a [http://www.indiana.edu/~spea/prospective_students/doctoral/job_placement/cox_michael.shtml previous CSSS student] studying the social structure of acequias and how they are both sustainable and vulnerable to novel disturbances. More academic work can be found [http://www.kcl.ac.uk/content/1/c6/04/70/19/WithnallDissertation.pdf here] discussing social structures. Most of this work has been qualitative traditional sociological work.

I've come across some data from the New Mexico Office of the State Engineer detailing acequia water rights infrastructure I think may be interesting to look at. Please see the spreadsheets on [http://www.nmacequiacommission.state.nm.us/acequia-list.html this page].

Cursory data analysis is a good place to start.

I'm eventually interested either crafting a model to simulate acequia network growth (theoretical) for historical research purposes, or some research into the statewide structure of acequias that may determine future policy recommendations (applied).

--------

"Roadkill as a means of spreading disease in Tasmanian Devils" ([[Gavin Fay]]) - Living in Tasmania, it is hard not to become familiar with the plight of the Tasmanian Devil, whose population is currently dwindling due to Devil Facial Tumour Disease (DFTD), a rather nasty infectious cancer which has become prevalent through much of the state. DFTD infection relies on transmission of infected cells from contact, most likely due to biting, which these critters do a lot of during mating and around prey carcasses. A hot conservation topic right now is forestry plans to build roads opening up a wilderness area in the north of the state to ecotourism opportunities. The devil population in this area has until now remained disease free.
There are concerns that the road will increase the likelihood that DFTD will spread to the diseasse-free population: Devils are scavengers and frequently feed on roadkill, the creation of a road may then provide an opportunity for increased frequency of contact between infected and disease-free devils. It might be interesting to investigate how introducing a fixed-location source of additional prey items (ie a road) to a devil population would change the contact network for Devils, and then also to what extent the increased contact frequency would have to be to facilitate transmission of DFTD from an infected devil population to a disease-free one.

--------

"Manage lots of fish stocks, or a few?" ([[Gavin Fay]]) - Australia's Southern and Eastern Scalefish and Shark Fishery (SESSF) is a multiple species fishery with a large number of vessels operating using a range of gears. The fishery exploits 80+ species, with a subset of target species managed by a total allowable catch (TAC) under a quota management system. Management of other species within the fishery is controlled by other measures such as trip limits, gesar restrictions, and spatial and seasonal closures. Specification of TACs requires data collection and routine stock assessment in order to calculate suitable catch limits given an assessment of stock status.

It is not feasible to perform full quantitative analyses for each quota species on an annual basis (from both a data perspective, instituional capacity, $$$, and other reasons) and rapid assessment methods are prevalent (or absent).
Given that the fishery is multiple species there exist a considerable number of technical interactions within the fishery. ie targeting one species leads to catch of several others - single fishing opportunities (shots, hauls) are not single species.

Given these interactions: Which species should we manage for? Are there a suite of species that we can actively manage for such that the risk to other stocks is not too great? Should we target the high-value species, abundant species (that may be low in value per kg but overall count big $), or manage to minimise the catch of vulnerable species? What are the effects of these options on ecosystem biomass, proportion of stocks in danger of collapse, yield, profit, etc?

Indeed, just describing the multispecies interactions (which species are associated with others in the data, how do these fishery assemblages vary over time and space (perhaps by port)), would be an exercise in itself. Perhaps one could also look at the relative costs to a port-based community associated with the fished assemblage shifting from one to another (perhaps as a result of climate change?).

* ([[Chaitanya Gokhale]]) If I understand the idea correctly I think this can be dealt with an evolutionary game theoretic approach. Although not completely, as per the reasons you have already stated, maybe we can abstract the system out to some important interactions for e.g. targeted catch of one species drags along some other species with it. I don't know if this makes sense, we can discuss it further next week.

--------

"Estimating abundance trends of non-target species" ([[Gavin Fay]]) - Trends in abundance of non-target, or bycatch species in fisheries is generally achieved by the results of fishery independent surveys. Surveys are expensive, and are not always available. How then can we estimate trends when these data are not available? Direct effects (ie incidental harvesting) can be measured (time series of catch), and it might be expected that the relative trends in exploitation rate of bycatch species should be similar to those target species with which the bycatch species are taken. This idea has been attempted in multispecies assessments under a 'Robin Hood' approach (steal from the data-rich to give to the poor). An issue is that the lack of information for the data-poor species can degrade the performance of the data-rich assessment, when the assessments are conducted simultaneously in a multispecies framework.

I'm thinking about a general multivariate state-space modelling framework for nontarget species, which could use correlations of direct effects with target species derived from fisheries logbook data, and the 'known' abundances and trends of the target species.
An additional question is how to quantify indirect effects of fishing on abundance of nontarget species. One possibility could be to guide the covariance with the results of foodweb modelling, which could be limited to simply describing how connected nontarget species are with the various target species. Another might be to use information about life history, or trophic level to describe general expectations for the degree of correlation/change.
It might be useful to make use of a system where it is possible to groundtruth methods - ie an ecosystem for which survey data are available. Alternatively, one could subset the data-rich species.

--------

"Evolution of life history strategies in sea lions" ([[Gavin Fay]]) - The Australian sea lion (ASL) is unique among the otariids (fur seals and sea lions) in that it exhibits a non-annual breeding strategy, with breeding cycle of ~17 months, an extended pupping season at rookeries of 4-5 months, and non-synchronous pupping among subpopulations (rookeries). In contrast, all other sea lions breed on 12 monthly cycle, with short pupping seasons, for which most species is synchronised among rookeries for the entire population.

A proposed idea is that the ASL strategy is in response to living in a low productivity environment (most other fur seals and sea lions live in highly productive, nutrient rich places). with the ability to vary the delay in implantantion of fertilised eggs depending on environmental conditions, thus enabling indiviudals to only invest in reproductive output when the probability for pup survival is high. Indeed, there is evidence that the length of breeding period is correlated with environemntal conditions.
Perhaps it would be neat to see whether the 2 different life history strategies observed are concordant with the hypotheses given evolutionary pressure. I am not familiar with the methods involved, but one could evolve a suite of life histories given different environmental regimes and see which survive?

--------

"Complexity: Friend or Foe ?" (Erik Van den broecke). I am setting up a new initiative – code name “The European Institute for Complexity Embracement”, that aims to foster “smart leadership” (read: complexity aware leadership) in business, government and academia. By mid July we will finalize the service portfolio. Per service we need to define the service value, service pricing and target groups. Furthermore high level service descriptions (process, techniques, tools) need to be described. As from mid July we will go to market.

Today we have identified four candidate services, namely: foresight, organizational performance, training on complexity related approaches and complexity awareness for leaders & decision makers.

First thing is to brainstorm on leadership/management related, complexity based, services.

* I'd be interested in discussing what (potentially) goes wrong if you do not take a complexity perspective [[User:Ligtvoet|Ligtvoet]]
-> That would be nice! To give you already some food for thought, I provide you a [http://files.me.com/erikvdb/bg4mgd/ link to the slide pack] on our initiative, regards, Erik Van den broecke
*([[Giovanni Petri]]) Same. I'm not sure I fully understand what you mean (as I'm not a biz/gov person) but I'd gladly discuss it further.
* First idea as a response to the slides is that this also reminds me of the idea of embracing uncertainty; this is e.g. propagated in the Real Options idea of financing projects. Basically, instead of seeing uncertainty (complexity) as a risk, it should be seen as an opportunity. This does require a change in decision makers' thinking, which is exactly what you suggest in the slides, right? I am working with some colleagues on a paper on buying/selling (the concept of) real options - we could parallel that with complexity. [[User:Ligtvoet|Ligtvoet]]
--------

"How do organisms use space?" ([[Andrew Hein]]). One fundamental problem in ecology and evolution is determining how and why organisms use space in the ways they do. Different organisms experience their environments at different “characteristic” spatial scales. For example, without the aid of technology, humans perceive and interact with their environments on the scale of meters (by sight) to kilometers (by sound or by walking from one place to another). Other organisms like bacteria perceive and interact with their environments on much smaller scales (e.g. micrometers). What determines these scales? Is it possible to predict the characteristic scale of an organism by knowing something about that organism? How do characteristic scales evolve and are they evolutionarily plastic or robust?

I envision two possible approaches to this problem. The first might be an evolutionary approach that assumes that characteristic scales evolve as a result of the need for organisms to communicate with one another. This would involve developing some evolutionary rules and allowing a network of organisms to “evolve” via simulations. These simulations could be used to understand the evolution and plasticity of characteristic scales. The second approach would be to try to understand what factors constrain the spatial scales used by different types of organisms. This might involve building some biological/physical models to try to predict how spatial scales ought to vary among organisms. These models could be compared to a data set on the spatial scales used by a broad variety of animals (I have one such data set).

* ([[Giovanni Petri]]) Sounds pretty cool if I get it right. Also, I'm interested in information spreading myself, this looks very relevant for other applications, e.g. couple information/transportation systems.

--------

"Does H1N1 make a comeback?" (Xin Wang). In the last half year of 2009 and at the beginning of 2010, H1N1 diseases swept the whole world including China. At that time the TV programs were all filled with such related news. Somebody said that it was the conspiracy, but whether or not it is true, we have to focus on what we should do to prevent some unknown disease from being pandemic because the sweeping of another unkown disease all over the world will occur sooner or later such as H5N1 and SARS in 2003. So analyzing the evolution of the virus from the molecular level combining with the spread of the disease in the population from the macro level may help us find the general way to prevent the concept virus from outbreaking.

Traditionally we use SIR, SEIR and etc. to model the spread of the disease. Here we may use the multi-agent-based method to model the virus including genes and protein, and human beings, and to simulate three processes, the first of the evolution of the virus, the second of interaction between human and virus, the third of the infection with people moving. Because of my background in mathematical control theory and game theory, not in molecule biology or ecology, I am short of knowledge on biology and I am not sure whether or not this idea is feasible. Maybe make some restriction from the biological view is necessary.

--------

Adding Genetics to Community phase-synchronization (Vane Weinberger)- Browsing through Spatial Food Webs literature, I ran into a paper that I loved since the minute I read it: although a little too old, Blasius and Stone (1999)[[http://www.lifesciences.tau.ac.il/departments/zoology/members/stone/documents/Chaosandphasesynchr...pdf]] simulated a simple tri-trophic ecological system that was able of the most incredibles fluctuations! I believe that this system can be expanded (maybe adding other relations into the local throphics phenomena), but what I REALLY wanted to add into the model was the population genetic subject: this work demostrate the great ammount of population crashes that are seen in a patch system and how they can be recovered when submerged on a spatial migrating system. However, as they are modelling the system from bottom-up approaches and thus adding the population-level processes of each guild, we could ask about how bad can these crashes affect the survival of the guild if we consider an Allee Effect or inbreeding phenomena. I do not know if someone has already done this before, but I think that this model would help us understand more about conservations efforts in the wild.

*([[Andrew Hein]]) This is a really nice idea. It would be interesting to try to track local and global oscillations in population genetic structure in the system you describe. It would also be interesting to try to determine the degree to which oscillations in genetic structure are synchronized (or out of phase) with population oscillations.

--------
Scale-Free Networks in intertidal communities - Network Topology effects on population structure (Vane Weinberger)- In 2005, Nowak's team demostrated that certain networks topologies could alter the random fixation of an allelle (simulated through the Moran Process). More precisely, they discovered networks with many hubs augmented the effect of natural selection. The intertidal system is known for its great ammount of sessile or limited dispersal animals that can only disperse through their larval stage. Therefore, it was believed that the genetic population structure of a population was mainly a function of their dispersal capabilities (as larvae). However, if there is a sexual-limited-contact of their progenitors, which could create a network topology with many hubs (it happens in some gastropods) it could happen that there is an effect of the network topology that could alter the genetic population despite the homogeneization of the larvae pool. (Notice the two different contact networks that are created though this simulation...that something that is also worth for studyin, I am sure this could happen in other systems!). I apologize: this idea was discussed a long time ago and I stopped browsing about how to taeckle the topic...but I am sure we could arrange something for this!

*([[Roberta Sinatra]]) I would be very interested. Actually I am working on a dynamical model to detect topological communities on graphs, ispired to how genotype of walkers mutate when they move on the graph, meet and interact. Although I am more interested in finding topological properties of the graphs, I think that a realistic model based on plausible biological and genetic assumptions can highlight interesting properties of some self-organized systems. We can have a chat about that!

---------
Modeling evolutionary dynamics of spatially structured populations ([[Felix Hol]]) -- I am very interested in the interplay between ecology and evolution. Motivated by Sewall Wright's seminal 1932 [http://www.blackwellpublishing.com/ridley/classictexts/wright.pdf paper] I would like to investigate the effect that metapopulation formation has on the speed of evolution. The computational model to investigate this could be based on work by Mitchell & Crutchfield (and coworkers) where a genetic algorithm evolves a population of cellular automata to perform a certain task (see this [http://www.pnas.org/content/92/23/10742.full.pdf paper]).
I propose to embed population structure in the genetic algorithm (GA) and find out what effect this has on the capabilities of the GA. One way of doing this might be to (bluntly) define subpopulations that cross breed at specified intervals; but I am sure that there are much more elegant/sophisticated ways of embedding structure. Some (wild) ideas for this are: putting them on graphs or lattices (with or without vacancies/movement)…. Any suggestions are greatly appreciated! (also other ideas for modeling stuff like this (evolutionary game theory etc..) are welcome)

* I have the same idea and I am thinking about how to train the initial structure to be the one robust to different situations. (Xin Wang)

---------
The self-generation of patterns in Five-in-Row Game (Xin Wang). In any human-machine or machine-machine game for chess, go, Five-in-Row and etc., the choice of patterns is very important, and so a good game-playing computer is always trained by both computer scientists and professional human players. After patterns are fixed, the weight of each pattern in the evaluation function can be optimized by NN, GA and other optimization methods. Although the depth of searching is another important factor, it only depends on fast searching algorithms and pruning algorithms. So the study on patterns makes sense to complex system. Traditionally the patterns are always fixed but here my initial idea is to train the computer to self generate its own patterns for use. This idea is very similar to "work by Mitchell & Crutchfield (and coworkers) where a genetic algorithm evolves a population of cellular automata to perform a certain task (see this [http://www.pnas.org/content/92/23/10742.full.pdf paper])." (see above part by Felix Hol).

--------
'''Network's shortest paths''' ([[Sergey Melnik]])

Consider a random network consisting of ''N'' nodes where each pair of nodes is connected with a given probability ''p'' ([http://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model see Erdos-Renyi random graph]). The question is about the shortest path through the network from one node to another (also called geodesic path, or intervertex distance):

Can we calculate analytically (and exactly) the probability distribution of shortest paths in such a network? That is, how likely it is that a pair of nodes chosen at random will be distance ''D'' apart. For distance ''D''=1 the answer is obviously ''p''. What are such probabilities for distances ''D''=2, ''D''=3, ''D''=4, etc.?

Note that the network has a finite number of nodes (which is not necessarily large) and there are only 2 parameters here, ''N'' and ''p''.
This is a simple yet fundamental question and there is much more to follow in terms of immediate applications and new theories once we answer it.

--------
'''The Monopoly project''' ([[Sergey Melnik]])

Have you ever wondered about the best strategy to play [http://en.wikipedia.org/wiki/Monopoly_%28game%29 Monopoly]?

We can start by answering simple questions such as "is it really better to be the first to throw the dice?", or "what are the most valuable squares on the field, and when?", or "to what extent do your skills help you overcome randomness to win this game?", or "how long would a game last?", or "how does all this changes with the number of players?". We can then go deeper to model negotiations and resource management strategies - plenty of possibilities here.

I am sure those who play this game already have some intuition. But can we precisely quantify these and other effects? I guess not yet. I think there is a lot here that can be modelled (analytically?) and compared with numerical (Monte Carlo?) simulations.

Finally, we can look into creating a new, even more exciting game to be played by the future generations. And surely you will have ''better calculated'' chances next time you play Monopoly with your friends!

--------

Sergey Melnik

2010-05-17T23:38:14Z

Sergey: New page: Here is a link to my homepage: http://www.ul.ie/sdcs/sergey more information will appear very soon...

Here is a link to my homepage:
http://www.ul.ie/sdcs/sergey

more information will appear very soon...

CSSS 2010 Santa Fe-Participants

2010-05-17T23:33:13Z

Sergey:

{{CSSS 2010 Santa Fe}}

[[Bruno Abrahao]] 
Cornell University

[[Nash'at Ahmad]] 
NASA

[[Lucas Antiqueira]] 
University of Sao Paulo

[[Andrew Banooni]] 
Yale University

[[Damian Blasi]] 
Instituto Balseiro, Bariloche

[[Jonathan Cannon]] 
Boston University

[[Oana Carja]] 
Stanford University

[[Kyla Dahlin]] 
Stanford University

[[Vessela Daskalova]] 
Queen Mary, University of London

[[Micael Ehn]] 
Mälardalen University

[[Gavin Fay]] 
University of Washington

[[Nicholas Foti]] 
Dartmouth College

[[Chaitanya Gokhale]] 
Max Planck Institute for Evolutionary Biology

[[John Paul Gonzales]] 
SFI Staff

[[Joseph Gran]] 
University of California, Davis

[[Julie Granka]] 
Stanford University

[[Andrew Hein]] 
University of Florida

[[Zoe Henscheid]] 
MITRE

[[Ana Hocevar]] 
Jozef Stefan Institute

[[Felix Hol]] 
Delft University of Technology

[[Anne Johnson]] 
NAVWARCOL

[[Daniel Jones]] 
Goldsmiths, University of London

[[Leif Karlstrom]] 
University of California at Berkeley

[[Mark Laidre]] 
Princeton University

[[Erika Fille Legara]] 
University of the Philippines, Diliman

[[Drew Levin]] 
University of New Mexico

[[Kimberly Lewis]] 
JWAC

[[Jing Li]] 
George Mason University

[[Andreas Ligtvoet]] 
Delft University of Technology

[[Dan MacKinlay]] 
University of South Australia

[[Thomas Maillart]] 
ETH Zurich

[[Thomson McFarland]] 
JWAC

[[Tracey McDole]] 
San Diego State University

[[Sergey Melnik]] 
University of Limerick

[[Megan Olsen]] 
University of Massachusetts, Amerst

[[Maria Opazo]] 
Columbia University

[[Anna Pechenkina]] 
Pennsylvania State University

[[Giovanni Petri]] 
Imperial College London

[[Griffith Rees]] 
Oxford

[[Florian Sabou]] 
Brown University

[[Katarzyna Samson]] 
University of Warsaw

[[Samuel Scarpino]] 
University of Texas at Austin

[[Lynette Shaw]] 
University of Washington at Seattle

[[Rajani R. Shenoy]] 
MITRE

[[Susanne Shultz]] 
University of Oxford

[[Roberta Sinatra]] 
Università degli Studi di Catania

[[Stephanie Sobek]] 
University of Western Ontario

[[Zhiyuan Song]] 
Stanford University

[[Yixian Song]] 
Darmstadt University of Technology

[[Bogdan State]] 
Stanford University

[[Michael Szell]] 
Medical University of Vienna

[[Ingrid van Putten]] 
CSIRO

[[Xin Wang]] 
Academy of Mathematics and Systems Science

[[Vanessa Weinberger]] 
Universidad Simon Bolivar

[[Sarah Wise]] 
George Mason University

[[Borys Wrobel]] 
Institute of Oceanology, Polish Academy of Sciences

[[Kang Zhao]] 
The Pennsylvania State University, University Park