CSSS 2010 Santa Fe-Blog
From Santa Fe Institute Events Wiki
|CSSS Santa Fe 2010|
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
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…
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 Because it is unpublished, I’ll check in with him periodically to discuss in more detail and see how the research is progressing as well as whether and when he might expect to publish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.
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.
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…
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.
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
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!
- It's a skill to explain difficult stuff in an easy way.
- Lots of dusting off of things I should know, but forgot.
- 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?
- 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.
- 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.
@Cowgirls. What's this ID thing about anyway? Don't I look old enough?
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.
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.
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.
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
Wednesday June 9
Today was a sad day for Dutch politics. Ligtvoet
Thank you Paige and Coco. 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!
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.
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:)
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
"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.
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 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.
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, 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, 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?
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!
Agent-based modelling is still a pretty new thing in sociology, and validation has always been a weak suit. Peter Hedström has 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 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).
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.
… 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 - 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.
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:
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...
This is a timely analysis of an interesting complex system. I personally like his results! ;-)
Cornell University professor predicts Brazil will win 2010 FIFA World Cup title His soccer study submits world's best teams to statistical analysis.
Nature's article: High hopes for Brazilian science
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)
Rides from Leroy (and Paige/Coco)
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
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 []. If you're interested in network statistics, just head to R-seek and search "networks". There are a bunch of network stats packages.
Ancient food webs with new issues to grapple with: Were species interactions structured differently in ancient vs. modern times? Apparently not that much. Although every link is a hypothesis based on inferences, if you have a fossil record like the Burgess shale(with soft tissue preservation)and an expert on ancient trophic interactions, you can create a food web with pretty high certainty (75% high certainty links in some cases). I was blown away by the research...got to get my hands on Dunne et al, 2008 PLOS Biology. Also, how cool would it be to go back in time and witness those crazy, experimental body pans, the evolutionary dead-ends?!
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
Today's my day, but I'm not really sure what to write. I'll just ramble...
I've been thinking a bit about what I'm supposed to get out of summer school. I think it's interesting that the answer to this question seems to be different depending on who I ask. Some people are here from the business sector, looking for commercial applications of complexity theory. Some are young grad students, brushing up on their theory. Others are more established, looking for ways to strengthen their dissertation. I personally find myself in between, looking for new and interesting ideas to pursue.
I'm not sure why I wrote that. I guess it's because I feel that while we're all here for different reasons, we can all achieve our goals in similar ways. A lot has been written about the daily lectures, and much discussion around the cooler seems to focus on them as well. I feel that somewhat misses the point of summer school. The classes are nice, but the real resource here in Santa Fe is ourselves.
Don't get me wrong, I'm all for informative lectures. I'm certainly one who gains knowledge quicker through directed learning. That said, I think it's important to remember that all (well, most) of the information provided in these lectures is available to us through many different means, most accessible from our own offices (or schools/businesses). On the other hand, the opportunity to interact with each other here, together and in person, is only available for the next week and a half.
It's kind of sad, because I feel like this environment here is the embodiment of what grad school should be. Unfortunately, summer school will end and we will return to work in semi-isolation back home.
So, I guess I'll wrap up by giving my probably misguided advice to those of us fortunate enough to be here... Make sure you take the time to a step back from the lectures and the projects and make use of the best resource available... your fellow students. I fear that if people spend the whole three weeks caught up in the tangible goals of CSSS 10, they'll miss the real opportunity, which is to talk to and interact with as many fellow students as possible while we're still here.
New Mexico is awesome.
I just cannot believe that anyone mentioned anything about Tom Carter's religion!!!. I mean, we have a confessed Darwinist around here (and I bet we all certainly are in a way or so), but com'on, FREEZBETERIAN!!!! I am changing religion after this lecture!! Thanks for this enlightening comment, Tom!!! .
"Memory is painful to me" (Cosma Shalizi)
I really liked the "Increase throughput until something SPECTACULAR happens" on a T-shirt. Maybe it could be added on the front anyway? Gotta ask Griff...
Vanessa: you ask, I deliver :). Seems Freezbetarianism gets some hits on google (a meager 2.89e5) but less than THE ONLY TRUE RELIGION, which has its own wikipedia page so there, IT MUST be true (like all those theorems in Greg's network). Anybody can see that pirates stand behind at least one complex system (and I am sure there's a power law there!). So unless you like stale beer, Vanessa, I really hope that The Great Monster touches you with His Noodly Appendages and you will see the truth: that FSM has greater balls than any flying disk, trade-marked or not. But going back to its main prophet (careful, may not be safe for work),..."Thou shalt keep thy religion to thyself...", I think that may not be such a bad idea after all...
Wednesday June 16
"Think of it as a big injection of beauty." -On Hyperbolic Geometry on networks
...on the other hand, religion and terrorism, state and religion... I am surprised the issue got so little response from the audience at Aaron's lecture. Although the discussion sure was great. I've been involved in popularizing science (in a Science Cafe format) for some time, trying to bring the interdisciplinary spirit to it...It was great to see how it is done by SFI. Anyway, I think I am reaching the point when I am so tired that I become hyperactive...It's a bad sign, but it's difficult to catch up with sleep (and I must confess, the slot after the lunch... difficult... many of us can be seen drifting away...) I think today was the day with most 'class' for me since a very long time, starting at 7 am with the Wonders of Mad Physics and ending at 9 pm with Aaron's. Thanks for great cofee at SFI!
A few quick links to interesting recent developments within the wider world of complexity.
- First self-replicating structure discovered in the Game of Life, the ubiquitous cellular automaton that I'm sure you're all aware of. And: a more focused assessment. It's runnable in Golly, which is an essential tool for anybody interested in exploring CAs, but is so vast that its runtime appears to be quite large...
- SocioPatterns are doing (consensual) tracking of various social settings using RFID tags. Just wish they would publish more of their data.
- Also just discovered that Newman's Networks bible has recently been finally published. It will be awaiting me when I return home.
Thursday June 17
Don't be somewhere else, when you are here!--Dan Rockmore
"What type of questions one asks are partly a function of personal taste and parttly constrained by the nature of the system and available data"--Jon Wilkins
Just find out that there was a lecture about origin of life during CSSS 2008
given by Eric Smith. There are slides on his website, in case anyone is also interested.
"...And suddenly there was a terrible roar all around us and the sky was full of what looked like huge bats, all swooping and screeching and diving around the car, which was going about a hundred miles an hour with the top down to Las Vegas. And a voice was screaming, 'Holy Jesus! What are these goddamn animals?'"
Fear and Loathing on the Santa Fe Trail
The obvious and fair question is what the hell does Hunter Thompson have to tell us about complex systems or doing science in general. Well, there's the obvious analogies of us screaming at a hundred miles an hour through the desert or that the freedoms many of us American's have been searching for did break like a wave and die somewhere east of Sacramento, but I think it's more subtle than that. Consider Nathan Eagle,"increase the entropy of your lives." Now assuredly he was being facetious, but in some ways I think he speaks directly to what motivated many of us to become scientists. Specifically, the overwhelming diversity and complexity of life and our universe. However, inherent in the complex systems that inspire us is the necessity to collaborate, a skill just as important as being able to analyze a system of differential equations, program in C++, or identify an Arabidopsis thaliana. Because without collaboration, And just like Raul Duke and his lawyer, we can often feel as though we are sitting in a room full of sheriffs who are going to expose us frauds at any time.
"If you ever happen to be corrected by Murray in any of the 3000 tongues of the world's 6000 that he speaks, you'll judge how successful his father was" Eric Smith on Gell-Mann
"Hey, how about Glottochronology?" Eric Smith again.
"That was a joke. I know". Yet again the man.
"I study english long time" Humble me.
"It needs a complex spell!! Uhuuhhhhhhhhh!" Alfred Hübler on vibrating a disk with sand.
"It's the chili" Alfred Hübler at the nth time he blew his nose near flammable materials.
"Haha! Nature calculates in decimal? No! But there's a bit of static friction! Lucky us!!!" Hübler again on the Lorenz watermill.
"I think we should stomp on Daniel's foot. No, maybe first throw him a ball and see if he reacts, then stomp him. I don't trust his injury, its all just made up for the gossip survey!" Felix after hours of coding.
"No, this would be an out-of-my-ass tree" Jon Wilkins in a moment of sci-poetry.
"You've just come in contact with the most important fact about infinity". Greig Leibon (presumably during caramel-induced high)
Today I learned that I hate C++, how to send a hall of linguists into a frenzy by proffering a single word ("Glottochronology!!!!", bahrhaahbaha and the skies opened etc etc), that pollen is usually not dangerous to humans and has no surface tension, cancer cells should be popped by super-strong electric fields that make superfew errors, more or less like super-jure. G'night.
Don't forget that in theory the same super-strong, but not too strong, electric fields can work as a contraceptive. Samuel_Scarpino
Santa Fe was nice, but I think I would have enjoyed the Baldy hike more. The mountains here are so different from the Alps I am used to (I wouldn't even call them mountains here). In Austria, when you go up a mountain, you see vegetation levels changing very rapidly, and the weather becomes more and more cold and unpredictable, starting below 2000m. Here, at 7.000 feet, there seem to be not many differences to lower altitudes. At least the Baldy hikers found some snow..
Early results from the gossip survey indicates that the topology of CSSS 2010 may resemble the below. Arguably not the most scientifically useful -- working on weighting edges and laying out in a more informative fashion -- but you can't deny we look hot in graph form.
Friday June 18
As a result of both formal research and our collective body of informal experiences, we presently have an enormous amount of information about the social world. With rare exception, however, we really do not have a widely supported conceptual framework that lets us systematically organize that information and effectively develop satisfying explanations of what makes the social world goes from it (nevermind coming up with solid predictions).
In Kuhn’s terminology, I don’t think it would go too far to say that the social sciences (perhaps other than economics) do not really have a strong paradigm anchoring the huge bodies of research they produce. Without the touch point of an agreed set of general principles, it becomes extremely difficult for the work that is produced to “talk” to each other in a coherent fashion. This makes the hope of building a body of cumulative knowledge about society very untenable. In lieu of that we just get a proliferation of parallel lines of thought that all attempt to explain pretty much the same thing based on vastly different pet ideas about how society works. Even a somewhat broad familiarity with the social sciences is enough to demonstrate the extraordinary number of times we’ve reinvented the wheel when it comes to social explanation.
Given this state of affairs, I think that advice we heard that cautions against overly ambitious attempts at porting models and explanations from one discipline into social research gains some added weight. In my opinion, what the social sciences need most is not another model of a particular social process or new ways of analyzing data. What they really need is coherency in perspective. I think in the end then, it is not necessarily going to be power-laws or simulation techniques that have the biggest interdisciplinary contribution to make to the study of the social world. Instead, I think it will just be a commitment to finding those paradigms that “cut nature at the joints” and allow us to say a lot of about the universe based on a few very simple but very powerful statements on how things are.
Evolutionary biology is one of those subjects that is intuitive enough for nonspecialists to grasp, varied enough to spend a lifetime studying, and cool enough that anyone would actually care to do either. The idea that life on Earth fundamentally changes the chemical properties of the atmosphere and the interpretation of the planet as part of the emergent system of life is awesome every time I think about it. The discussion of anthropogenic climate change (at least in the United States) seems to suggest that life on Earth has doomed itself as never before, which is probably what plants felt as CO2 levels declined 500 million years ago (or as they would have felt had they had cognitive processes). It will be interesting to see how organisms with agency and the capability of self-organization respond to an environment we deem increasingly hostile.
Also, I am guessing no one else was really excited about the section of Doug Erwin's talk regarding Virginia oysters, but I was! I don't particularly like oysters, but I do like pre-1600 Virginia history. I've read that people have started to create fake oyster reefs in an attempt to promote this original water filtration system. Kind of interesting? Oyster restoration!
(Saturday June 19)
(Sunday June 20)
Monday June 21
Here's a complex adaptive agent-based system for you - morning birdsong outside St John's
Sorry there's no embedded sound player - the wiki doesn't like sound files.
If that's not analytic enough, here are some other links of relevance about crazy big data and complexity in interdisciplinarity:
- a More lurid social media network analysis than we have seen so far - Brazilian prostitution website data applied to HIV epidemics
- if you hadn't noticed the comic-strip "interdisciplinary" zeitgeist, you shoudl checkout
- From the Antipodes, a Cellular automata-driven artist who Dave Noyze, and,
- my most recommended link for this trip - Greg Wilson's awesome Software carpentry course from UToronto ´is available freely online. As the man himself says:
- Computers are as important to modern science as telescopes and test tubes. Unfortunately, most scientists are never taught how to use them effectively. After a generic first-year programming course, most scientists have to figure out for themselves how to build, validate, maintain, and share complex programs. This is about as fair as teaching someone arithmetic and then expecting them to figure out calculus on their own, and about as likely to succeed.
After spending all of yesterday messing around with trying to get bone-headed academic software to compile, I'm inclined to agree with him.
Wow, beginning of the last week. I think we have all learned a lot so far, with time still left to learn and do more! I was discussing with with some other students this weekend about the things we learned: free coffee at 7:50PM in the cafe (maybe I shouldn't give away this secret quite yet?), green chili is spicier than red chili, it's easy to sunburn at 7000 feet, pink pie is scary and shouldn't be eaten (Ok, Ok, this one was from tonight), it is possible but not particularly nice on the feet to walk back to SJC from Cowgirl, almost everything is cheaper at the flea market than in town, and people will gossip about anything including a dislocated/broken toe. Another student even got to do their own laundry for the first time! I call that a success.
But in all seriousness, we have learned quite a bit even if it feels like information overload at times. I'm sure we've all had lectures where we felt more at home than others, but that's the beauty of the field of complex systems: it applies everywhere, and the possibilities are huge! We've also gained additional experience in working with people from other fields, and managing meetings of eight distinct viewpoints and (human or scientific) vocabularies. Much of what we have learned we probably won't even realize fully until we return to our home institutions and work on our research, teach classes, or do our jobs. Thinking about complex systems and how to analyze them will affect how we think about problems, and the contacts we have made here will help shape our entire careers. Or at least, I hope that will be true for myself! I look forward to keeping in touch with all of you.
Also, we apparently have a low probability of any additional injuries if you're willing to make the assumption that individual injuries are not independent events. According to Tom they average about one injury per week at CSSS and since we already have our three, feel free to have fun! Unless you're a stickler for probabilistic details, of course. Either way, you can rest assured that we are not any more accident prone than our predecessors.
I was really scared about this task at the beginning of the course (writing in the blog, brrrrr). I saw that Dan Rockmore arbitrarly wrote my name next to a bunch of other names that 'I did not know' by that time....and now here I am, thinking: Well that's great, Megan (my project-partner) is writing right next to me, and see, I just spend the whole weekend with Johnathan (yes yes, Johnathan, I keep writing wrong your name, I do not know why I keep putting the extra 'h'!! By the way, how was that new trip to the hot springs?)!!!
Now I realize the amazing work that SFI CSSS does...we are not only taught by most of the tops researchers in the world, but we can actually experience how dynamics (e.g social in this particular case) are created by own flesh!!! And yes, Daniel's network is the most compelling evidence we have for that....and yes, we look AMAZING in the network, I just cannot wait to see that project's results.
I aso noticed that Alfred Hubler left a big impression on us...everyone has commented about him...so I will copy everyone's behavior and add that he is one of the most amazings teachers I have ever had: I have not seen in a long time someone who has such passion for teaching and/or just do research! I think my goal in life is to become such a fan of my work as he is for his own....and for me, that is one of the most important lessons I had from this summer course. I actually hope that we can all be like him and we can still gather in the future, continue doing integrative research and reminisce about this SFI CSSS 2010, where we all met.
Tuesday June 22
Some wisdom from this morning:
"To the physicists, I'm ignoring Boltzmann's constant...to everyone else, ignore that." - C. Moore
"Protein folding is an NP-Hard problem. Are your ribosomes solving NP-Hard problems? No, because if they were you'd be dead." - C. Moore
--Samuel_Scarpino we're?.... you study english long time. **see history**
I can't believe that we only have a day of lecture left in our schedule and three days left before we go toodle-ooing. Time just went by so swiftly! It seems like it's only yesterday when I was solitary and having my first dinner at the coffee shop when Lucas came up to me and introduced himself and invited me over to their table (he was with Felix and Florian). :-) I never thought that I'd be very much enjoying my stay here. Yes, I expected to learn a lot from the summer school; but no, I didn't really imagine myself to have this much fun (since the invitation letter said "intensive training"). I have to admit that at the start I was so intimidated by the summer school (the topics, the lecturers and my co-participants); it's my first time to leave my country so everything was just so overwhelming. But much to my surprise, everyone was just so nice, friendly, understanding and very accommodating!
Needless to say, I have learned a great deal from a wide range of stuff. It is such a privilege to be here studying complex systems science, coding numerical models, chatting, eating, hiking, dancing, shopping, doing laundry, whining, and well, getting drunk, with the smartest people I've ever met. In my homepage, I said that "I like working with people who are critical and have different perspectives than mine and yet not too arrogant to settle between ideas." And that "I am always excited to learn new stuff especially from academic peers." And that I love working with creative and constructive individuals who are both happy and secure with themselves and with what they know and ones who definitely know how to have fun... Well, what can I say? This is indeed the place to be.
Looking forward to Friday. I am quite excited to hear and learn more about everyone's projects! But more importantly, I'm psyched about the going-away party, which I believe would be "infused with all our kick-ass interdisciplinary awesomeness."
As the "hypothesis of my parents" (Krakauer), I wonder who the null model is (or was) and what my p-value might be.
I have heard on several occasions of late that what natural resource management is most in need of is more theory development. Most work tends to be centered on incrementally advancing applied scientific tools, often driven strongly (and understandably) by earning imperatives.
This reminds me, as has the CSSS, of the value of time to think. And indeed, the joy that comes with using that time to think about Science. With a capital S.
While Complex Systems approaches have only just begun to be applied within natural resource management, the summer program has seen me think many crazy thoughts of how one would connect some of the material to the issues I face on a daily basis back in the real world. Persuading someone to fund these remains my task. Many have commented on the incredible opportunity of attending and being part of the summer school. With the tin man reference the other day, I will simply say that us scarecrows now have a lot more straw stuffed into our heads. Emergent properties pending?
To our coffee shop coders, I offer you this.
Reflecting on the multidisciplinary nature of things, language evolution and economics clearly co-exist.
And with regard to Chaitanya's excellent tutorial on evolutionary game theory, we have 'rock paper scissors lizard Spock'.
My favorite movies on Complexity
1) Jacob Bronowski's The Ascent of Man is a BBC thirteen part series produced in 1973. The connection between the writer and host, Bronowski, with complex systems is even more interesting. Bronowski was a gifted mathematician who received a Ph.D. from University of Cambridge in 1935. He showed great promise as a pure mathematician, working with John von Neumann and other major characters in the mathematical scene at the time. After the war, however, his interests turned towards multidisciplinary research and complex systems, when he was given the task of analyzing the Taung child's fossilized skull to estimate its age and discriminate its features from those of apes, using statistical analysis. Among his research topics, he studied biology to understand the nature of violence, and the role of imagination and symbolic language in the progress of scientific knowledge. The tragic part is that this kind of complex systems research was not in fashion at the time. As a result, Bronowski has never received recognition for his pioneer career as a multidisciplinary scientist as he potentially would otherwise as a mathematician.
2) Carl Sagan's Cosmos: A personal voyage (1980). This series was inspired on and share the producer of The Ascent of Man. It was the most watched TV series in the history of American TV until The Civil War (1990). Not only is its content fantastic, but it also has an amazing quality. My first contact with the series happened when I was 5, and I've been rewatching it many times since then. The series served as my main inspiration to become a scientist. Sagan was a Cornell professor who passed away in 1996, after fighting with a rare form of cancer. As a Cornell student, I feel a great honor to walk in the halls he once did.
This is not exactly on my list of favorites, but I came across this interesting Ted talk by George Whitesides on complexity/simplicity. He has some amusing and some interesting points. For example, he explains how to start a conversation with a Physicist at a dinner table: just start with the words "complexity" and "emergence" and then daydream about other things! :-) His definition of complexity is also interesting. He mentions that it is possible to understand a lot about Bill Gates. And so it is about U2's Bono Vox. Complexity is what you get when you try to understand the interaction between the two!
I saw the naive question on facebook again:" Why are there apes in the zoo if we humans originated from apes?" Well, it is a bad joke.
Jessica Flack gave an interesting lecture on her studies on primate behavior. Why are there so many people, not only biologists but also anthropologists and psychologists, interested in studying primate behavior? A simple reason is that we want to understand better human behavior, and quite often, people just can't stop comparing themselves with other animal species and asking the question why humans are so unique. Maybe it is more appropriate to ask if humans are indeed unique in one way or another, depending on what you are keeping in mind or what you read, e.g., Why We Cooperate (M. Tomasello) vs. The Age of Empathy (F. de Waal).
We naturally expect something from evolution. "Evolutionary Psychologists" claimed that human behavior is hard-wired in genomes through the selection during the Stone Age, but it doesn't help answer the question at all as we know too little about our ancestors' behavior. So, the best we can do is to observe our close kin species carefully and to figure out what there is in common. When I was in my primary school, the textbook taught me that the key distinction between humans and other apes was that we can make tools. But this is no longer true. Thanks to empirical studies on this topic, we now know that chimps are quite smart and have the ability to make and use simple tools, they can recognize themselves in the mirror, and they have empathy onto others at least in some situations. On the other hand, chimps are aggressive, they are cannibals and they are often on the warpath. Can these evidence from chimps justify similar human behavior? Be careful. Do not forget the other closest species to humans, bonobos. They look similar to chimps, but their behavior is quite different -- much less aggressive, so to speak.
In general, human behavior should be somewhere between the rational agents in neoclassical economics and the 0-intelligence particles in econophysics. And hopefully, we can converge to the true value from different directions.