Santa Fe Institute Events Wiki - User contributions [en]

Photos

2006-06-28T22:38:38Z

Greg:

{{CSSS 2006 Santa Fe}}

All contributions welcome! Do not forget witful subtitles ;-)

We could do one page per event. When posting into an event, just indicate your name and number of photo posted on each line pointing to the event.

*[[June_11-Sunday_3PM-Tent_Rock_Park|June 11th-Sunday 3PM-Tent Rock Park]]: Fabrice (3) + Group Photo (Andrea?)
*[[June_18-Saterday_9PM-Peak_Mountain_Hiking|June 17th-Saturday 9PM-Peak Mountain Hiking]]: Fabrice (3)
*[http://www.flickr.com/photos/99405883@N00/sets/72157594170233125/ June 17th-Saturday Softball]: Kate (50-some-odd)
*June 18th-Sunday VLA: [http://www.flickr.com/photos/tamasmakany/sets/72157594171440953/ Tamas (32)]
*June 18th-White Sands: [http://www.flickr.com/photos/tamasmakany/sets/72157594171444136/ Tamas (38)]
*June 18th-More White Sand:
[http://www.flickr.com/photos/14353139@N00/sets/72157594180809378/ Cornelia(60)]
*June 21th-Wednesday Bela Fleck Concert: [http://www.flickr.com/photos/tamasmakany/sets/72157594175912358/ Tamas(52)]
*June 27th-Sunday Night Life Movies (MPlayer):
[http://complex.upf.es/~andreea/CSSS06/Movies/DSCI0007.ASF] [http://complex.upf.es/~andreea/CSSS06/Movies/DSCI0011.ASF] [http://complex.upf.es/~andreea/CSSS06/Movies/DSCI0012.ASF]
[http://complex.upf.es/~andreea/CSSS06/Movies/DSCI0014.ASF]
[http://complex.upf.es/~andreea/CSSS06/Movies/DSCI0015.ASF]

I'm going to have to break with Fabrice's format, since all of mine are together, but if you follow the first or second link, they tell a story!
I update the page every day, so check back to see more photos.
*[http://www.flickr.com/photos/99405883@N00/sets/72157594158012860/ A selection of Kate's Santa Fe photos] (look near the bottom for new ones)
*[http://www.flickr.com/photos/99405883@N00/sets/72157594167225426/ Kate's Blue Doors](ditto)
*[http://www.flickr.com/photos/99405883@N00/ All of Kate's Santa Fe photos](new ones at the top)

A few pics from my first film, more to come. Greg.
[http://www.flickr.com/photos/35687925@N00/]

SFSS 2006 After Hours

2006-06-21T17:59:00Z

Greg:

{{CSSS 2006 Santa Fe}}
Please keep a roughly chronological order, delete postings after the activity is finished, and post dates and times.

==Music==
* Bela Fleck and the Flecktones will be in concert in Santa Fe on Wednesday night (21 June). 5 30 PM. Check out the forum [http://www.santafe.edu/forums/showthread.php?t=300 thread]
Tickets available [http://purchase.tickets.com/buy/TicketPurchase?organ_val=2274&agency=tdc&schedule=list here]

Contact : Ryan Woodard

* Thur. June 22, the group Ferintosh will be in Santa Fe. They play mostly Scottish Baroque and Cape Breton music.

The GiG 8:00 PM
1808 Second Street (next to the Second Street Brewery)
Suggested contribution $15 at the door.
Checkout the forum [http://www.santafe.edu/forums/showthread.php?t=239 thread]

Contact : Ryan Leary

==Basketball==
* Thursday, 7pm in the gym

==Taos & Corn Dance Festival==
* June 24th (Saturday) - Taos & Corn Dance Festival
w/ car: Hana (4)

wo/ car?: Andreaa, Ryan, Elham, Harry, Sam, Sandra, Cornelia, Andrew, Alessandro, Fabrice, Nikhil, Patrick, Valentin, Heinz, Andrea, Jorge, Greg.

==Other trips==

* June 23/24-25th - Grand Canyon (suggested trip) [interested?: let saskia.werners know at wur.nl]

==Provisioning==
* Grocery & Supply run to town

==Farther Away Hiking/Sightseeing trips==
Sometime in the near future...
The [http://kevingong.com/Hiking/TentRocks.html Tent Rocks] trip on June 11 was awesome!!! Hiking folks, you would love it! And it is 40min away! (Andreea)

==Hiking locally==
Recommended:
'''Deception Point, Lake Peak & Penitente summit Loop.''' Starts from Santa Fe ski bowl (car required). Day hike up Winsor trail and Raven's Ridge with serious views, some scrambling along minimally exposed ridge from Deception to Lake Peak. Various return legs including skipping Lake and direct back down ski slopes, skipping Penitente for off-piste scramble to Nambe Lake and ramble over Penitente summit wildflower meadow then reconnect with the Skyline Trail and on back down an easy cruise through forest shade. Boots strongly recommended for scrambling; 2+ liters minimum water/person.

[16 June 06] "Day Hikes in the Santa Fe Area," by the Sierra club, is available in the Fireside room...

Games and nets literature review

2006-06-21T17:56:10Z

Greg:

Back to [[Games and networks]]

'''Literature'''

'''Eguilez, V. ''et al.'' Cooperation and emergence of role differentiation in the dynamics of social networks. ''arXiv: physics'' (2006) [http://arxiv.org/pdf/physics/0602053 pdf]

I found this paper describing a very similar model and I believe this is more or less what we intend to do.
On this model agents play the PD in a network structure. More or less it goes like this; Links between Defector and defector break and are randomly assigned. Rules (when playing PD) between the agents are adapted by imitating the wealthiest neighbor (this would be adaptation within the agents lifetime (learning), there is no evolutionary adaptation as we discussed in the evening meeting, which we could also implement and compare both).
Their result is some role differentiation between the agents (leaders, conformist, exloiters, etc). Their treating the problem "how the network is dynamically formed or how a given network structure is reached after social agents interact for a long time".

'''Ohtsuki, H., Hauert, C., Lieberman, E. & Nowak, M.A. A simple rule for the evolution of cooperation on graphs and social networks. ''Nature'' 441: 502-505 (2006).''' [http://www.santafe.edu/events/workshops/images/e/e0/OhtsukiEtAl06.pdf pdf]

This is a simple exploration of how network structure -- in particular,
connectedness -- affects the evolution of cooperation. They find that a good
predictor for whether cooperation can invade and spread in a network is whether
the benefit-cost ratio is greater than the (average) degree of the graph. They
derive the result exactly for a cycle, approximately for a random graph where
every node has the same degree, and use simulation to show that the fit is good
for true random graphs and scale-free networks.

'''Santos, F.C., Pacheco, J.M. & Lenaerts T. Evolutionary dynamics of social dilemmas in structured heterogeneous populations. ''Proc Nat Acad Sci USA'' 103: 3490-3494 (2006).''' [http://www.santafe.edu/events/workshops/images/5/58/SantosEtAl06.pdf pdf]

The authors show that heterogeneity in the degree of the graph (e.g. scale-free networks as opposed to single-scale networks) can encourage the evolution of cooperation. They simulate using what amounts to an imitation rule on a fixed network structure, and parameterize the game that is played so that it can represent three popular games: Stag Hunt, Hawk-Dove, and Prisoner's Dilemma.

'''Page, K. Nowak, M. Sigmund, K. The spatial ultimatum game. ''Proc. R. Soc. Lond. B'' 267, 2177-2182 (2000)''' [http://www.santafe.edu/events/workshops/images/8/85/Page_-_spatial_ultimatum_game.pdf pdf]

In an ultimatum game played between members of a population with random mixing offer strategies evolve towards zero, provided the mutation rate per generation is small. On a 1D lattice they approximate a fair split, and on a 2D grid they are around 0.35.

'''Goyal, S. Learning in Networks: a Survey. ''Forthcoming in, Group formation in economics: networks, clubs, and coalitions (2003)'''
[http://www.santafe.edu/events/workshops/images/0/04/Goyal_2003.pdf pdf]

A broad overview of learning on both static and adaptive networks. The paper examines a variety of games including those involving information aquisition, information sharing, cooperation, conflict and others.

'''Jin, E., Girvin, M. and Newman, M. Structure of Growing Social Networks ''Physical Review E (2001)'''
[http://www.santafe.edu/events/workshops/images/1/12/Girvan_and_Newman_2001.pdf pdf]

Some interesting ideas in general, but specifically useful for thinking about how to model the growth and decay of social networks. Also, since this is co-authored by Mark Newman it would be convenient to ask him about the ideas put forth in the paper.

'''Not yet read:

'''Nowak, M. and Sigmund, K. Evolutionary dynamics of biological games. ''Science'' 303 (2004)'''
[http://www.santafe.edu/events/workshops/images/0/0d/Nowak_sigmund_-_evolutionary_dynamics_of_biological_games.pdf pdf]

'''Albert, R. and Barabási, A. Topology of Evolving Networks: Local Events and Universality ''Physical Review Letters'' (2000)'''
[http://www.santafe.edu/events/workshops/images/b/bb/Albert_and_Barabasi_2000.pdf pdf]

'''Jackson, M. and Wolinski, A. A Strategic Model of Social and Economic Networks ''Journal of Economic Theory'' (1996)'''
[http://www.santafe.edu/events/workshops/images/9/9c/Jackson_and_Wolinski_1996.pdf pdf]

'''Bala, V. and Goyal, S. A Noncooperative Model of Network Formation ''Econometrica'' (2000)'''
[http://www.santafe.edu/events/workshops/images/f/f0/Bala_and_Goyal_2000.pdf pdf]

'''Social Foraging

'''Rogers A. Does biology constrain culture? ''American Anthropologist'' 90(4): 819–831 (1988).'''
[http://www.santafe.edu/events/workshops/images/b/b7/Rogers_1988_-_Does_biology_constrain_culture.pdf pdf]

Rogers shows that in a population with both individual learning strategies and social learning strategies, for certain probabilites of environmental change in any given generation, the mixed evolutionarily stable strategy will be at a point at which the payoff from social learning exactly matches that of individual learning. Individual learning is assumed to have a constant, frequency independent payoff. He assumes individual learning to have a cost associated with it and social learning to be costless. The model has no space or other structure across which animals communicate. If the environment changes with too great a probability per generation social learners will be eliminated.

'''Wakano, J. Aoki, K. and Feldman, M. A mathematical analysis of social learning ''Theoretical Population Biology'' 66 249–258 (2004) [http://www.santafe.edu/events/workshops/images/0/0b/Wakano_Aoki_Feldman_2004_-_Evolution_of_Social_Learning%3B_a_mathematical_analysis.pdf pdf]

The authors present a model in which social learning, individual learning and fixed (genetic) strategies are in competition. Social learning has cost ''d'', individual learning has cost ''c'' and making a mistake about the state of the environment has cost ''s''. Costs are ordered ''d < c < s''. The fitnesses of the different strategies vary as a function of the number of generations between environmental changes ''l''. Individual learners win when the environment changes every generation (''l'' = 1), decreasing in frequency as the number of generations between changes increases. Social learners are at zero frequency when ''l'' = 1, rising in frequency while ''l'' < 684. When ''l'' > 684 innate strategies suddenly rise from zero frequency to take over the whole population. This critical value of ''l*'' = 683 is for a given set of parameters .

'''Dall, S. ''et al.'' Information and its use by animals in evolutionary ecology. ''TREE'' 20 4 (2005)'''
[http://www.santafe.edu/events/workshops/images/6/66/Dall_et_al_2005_-_Information_and_its_use_by_animals_in_evolutionary_ecology.pdf pdf]

This paper includes a section on 'inadvertant social information' - ie cues. The authors mention that use of social cues can lead to informational cascades - there's a literature in economics on this that I know exists but haven't read much of. This can be valuable, but can also lead to important errors. An examples among animals is the take-off behaviour of large flocks of birds. Many of the birds in a departing flock will take off on the basis of only social cues from the birds around them - this may be valuable if it usually signifies approaching danger, but a waste of energy if it does not. The sharing of information through social cues has useful emergent group level results such as 1. the synchronisation of patch departure 2. the rapid learning of local habitat depletion 3. the estimation of habitat or bredding colony quality (eg from observation of the number of offspring fledged in various colonies). There are likely to be costs involved in both types of information collection (social and individual) and as a result it may pay to specialise in one or the other. Information pooling among social insects is heavily studied, often in haplodiploid species such as ants or bees.

'''Liu, Y. Passino, K. Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors. ''JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS'' Vol. 115, No. 3, pp. 603–628 (2002)''' [http://www.santafe.edu/events/workshops/images/7/79/Liu_2002_-_Biomimicry_of_Social_Foraging_Bacteria.pdf pdf]

An evolutionary simulation of bacterial social foraging by means of 'attractants' they secrete in space and which others respond to. Extending this with explicit networks might be exciting.

'''Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele et al.'''
[http://www.santafe.edu/events/workshops/images/0/03/Social_network_growth_Catanzaro.pdf pdf]

Using a variant on the “BarabHasi–Albert preferential attachment” model the authors reproduce some of the assortative qualities of social networks. Their variation includes a greater level of mixing as the life of the node is > than that of the edge. It is demonstrated that strong assortativity can break the scale free nature of the networks.
(this could be of interest for the consequences of clustering strategies in the proposed model)

'''Lieberman, E. Hauert, C. Nowak, M. Evolutionary dynamics on graphs. ''Nature'' 433 (2005)
[http://www.santafe.edu/events/workshops/images/5/58/Lieberman_nowak_sigmund_-_evolutionary_dynamics_on_graphs.pdf pdf]

The authors investigate the consequences of sub structuring in a population using a graph theoretic approach. They observe that the structure can promote drift over selective processes relating to gene fixation. Where multiple roots or origins exist in the graphs mutants occurring in these nodes may never fixate or go extinct. Most interestingly they investigate whether graphs exist that could have the opposite effect. They find that graphs can be produced where there fixation probability of advantageous mutations approaches unity, all but eliminating drift in sufficiently large poulations.
(the consequences of amplifiers and suppressors of natural selection occurring in networks are huge. Under what conditions and processes do populations increase their evolvability, making a transition between the dominance of evolutionary processes?? They also look at a game played on a cyclic network with a simple pay of matrix on pages 314-5.)

Back to [[games and nets group]]

Games and nets literature review

2006-06-21T17:54:25Z

Greg:

Back to [[Games and networks]]

'''Literature'''

'''Eguilez, V. ''et al.'' Cooperation and emergence of role differentiation in the dynamics of social networks. ''arXiv: physics'' (2006) [http://arxiv.org/pdf/physics/0602053 pdf]

I found this paper describing a very similar model and I believe this is more or less what we intend to do.
On this model agents play the PD in a network structure. More or less it goes like this; Links between Defector and defector break and are randomly assigned. Rules (when playing PD) between the agents are adapted by imitating the wealthiest neighbor (this would be adaptation within the agents lifetime (learning), there is no evolutionary adaptation as we discussed in the evening meeting, which we could also implement and compare both).
Their result is some role differentiation between the agents (leaders, conformist, exloiters, etc). Their treating the problem "how the network is dynamically formed or how a given network structure is reached after social agents interact for a long time".

'''Ohtsuki, H., Hauert, C., Lieberman, E. & Nowak, M.A. A simple rule for the evolution of cooperation on graphs and social networks. ''Nature'' 441: 502-505 (2006).''' [http://www.santafe.edu/events/workshops/images/e/e0/OhtsukiEtAl06.pdf pdf]

This is a simple exploration of how network structure -- in particular,
connectedness -- affects the evolution of cooperation. They find that a good
predictor for whether cooperation can invade and spread in a network is whether
the benefit-cost ratio is greater than the (average) degree of the graph. They
derive the result exactly for a cycle, approximately for a random graph where
every node has the same degree, and use simulation to show that the fit is good
for true random graphs and scale-free networks.

'''Santos, F.C., Pacheco, J.M. & Lenaerts T. Evolutionary dynamics of social dilemmas in structured heterogeneous populations. ''Proc Nat Acad Sci USA'' 103: 3490-3494 (2006).''' [http://www.santafe.edu/events/workshops/images/5/58/SantosEtAl06.pdf pdf]

The authors show that heterogeneity in the degree of the graph (e.g. scale-free networks as opposed to single-scale networks) can encourage the evolution of cooperation. They simulate using what amounts to an imitation rule on a fixed network structure, and parameterize the game that is played so that it can represent three popular games: Stag Hunt, Hawk-Dove, and Prisoner's Dilemma.

'''Page, K. Nowak, M. Sigmund, K. The spatial ultimatum game. ''Proc. R. Soc. Lond. B'' 267, 2177-2182 (2000)''' [http://www.santafe.edu/events/workshops/images/8/85/Page_-_spatial_ultimatum_game.pdf pdf]

In an ultimatum game played between members of a population with random mixing offer strategies evolve towards zero, provided the mutation rate per generation is small. On a 1D lattice they approximate a fair split, and on a 2D grid they are around 0.35.

'''Goyal, S. Learning in Networks: a Survey. ''Forthcoming in, Group formation in economics: networks, clubs, and coalitions (2003)'''
[http://www.santafe.edu/events/workshops/images/0/04/Goyal_2003.pdf pdf]

A broad overview of learning on both static and adaptive networks. The paper examines a variety of games including those involving information aquisition, information sharing, cooperation, conflict and others.

'''Jin, E., Girvin, M. and Newman, M. Structure of Growing Social Networks ''Physical Review E (2001)'''
[http://www.santafe.edu/events/workshops/images/1/12/Girvan_and_Newman_2001.pdf pdf]

Some interesting ideas in general, but specifically useful for thinking about how to model the growth and decay of social networks. Also, since this is co-authored by Mark Newman it would be convenient to ask him about the ideas put forth in the paper.

'''Not yet read:

'''Nowak, M. and Sigmund, K. Evolutionary dynamics of biological games. ''Science'' 303 (2004)'''
[http://www.santafe.edu/events/workshops/images/0/0d/Nowak_sigmund_-_evolutionary_dynamics_of_biological_games.pdf pdf]

'''Lieberman, E. Hauert, C. Nowak, M. Evolutionary dynamics on graphs. ''Nature'' 433 (2005)
[http://www.santafe.edu/events/workshops/images/5/58/Lieberman_nowak_sigmund_-_evolutionary_dynamics_on_graphs.pdf pdf]

'''Albert, R. and Barabási, A. Topology of Evolving Networks: Local Events and Universality ''Physical Review Letters'' (2000)'''
[http://www.santafe.edu/events/workshops/images/b/bb/Albert_and_Barabasi_2000.pdf pdf]

'''Jackson, M. and Wolinski, A. A Strategic Model of Social and Economic Networks ''Journal of Economic Theory'' (1996)'''
[http://www.santafe.edu/events/workshops/images/9/9c/Jackson_and_Wolinski_1996.pdf pdf]

'''Bala, V. and Goyal, S. A Noncooperative Model of Network Formation ''Econometrica'' (2000)'''
[http://www.santafe.edu/events/workshops/images/f/f0/Bala_and_Goyal_2000.pdf pdf]

'''Social Foraging

'''Rogers A. Does biology constrain culture? ''American Anthropologist'' 90(4): 819–831 (1988).'''
[http://www.santafe.edu/events/workshops/images/b/b7/Rogers_1988_-_Does_biology_constrain_culture.pdf pdf]

Rogers shows that in a population with both individual learning strategies and social learning strategies, for certain probabilites of environmental change in any given generation, the mixed evolutionarily stable strategy will be at a point at which the payoff from social learning exactly matches that of individual learning. Individual learning is assumed to have a constant, frequency independent payoff. He assumes individual learning to have a cost associated with it and social learning to be costless. The model has no space or other structure across which animals communicate. If the environment changes with too great a probability per generation social learners will be eliminated.

'''Wakano, J. Aoki, K. and Feldman, M. A mathematical analysis of social learning ''Theoretical Population Biology'' 66 249–258 (2004) [http://www.santafe.edu/events/workshops/images/0/0b/Wakano_Aoki_Feldman_2004_-_Evolution_of_Social_Learning%3B_a_mathematical_analysis.pdf pdf]

The authors present a model in which social learning, individual learning and fixed (genetic) strategies are in competition. Social learning has cost ''d'', individual learning has cost ''c'' and making a mistake about the state of the environment has cost ''s''. Costs are ordered ''d < c < s''. The fitnesses of the different strategies vary as a function of the number of generations between environmental changes ''l''. Individual learners win when the environment changes every generation (''l'' = 1), decreasing in frequency as the number of generations between changes increases. Social learners are at zero frequency when ''l'' = 1, rising in frequency while ''l'' < 684. When ''l'' > 684 innate strategies suddenly rise from zero frequency to take over the whole population. This critical value of ''l*'' = 683 is for a given set of parameters .

'''Dall, S. ''et al.'' Information and its use by animals in evolutionary ecology. ''TREE'' 20 4 (2005)'''
[http://www.santafe.edu/events/workshops/images/6/66/Dall_et_al_2005_-_Information_and_its_use_by_animals_in_evolutionary_ecology.pdf pdf]

This paper includes a section on 'inadvertant social information' - ie cues. The authors mention that use of social cues can lead to informational cascades - there's a literature in economics on this that I know exists but haven't read much of. This can be valuable, but can also lead to important errors. An examples among animals is the take-off behaviour of large flocks of birds. Many of the birds in a departing flock will take off on the basis of only social cues from the birds around them - this may be valuable if it usually signifies approaching danger, but a waste of energy if it does not. The sharing of information through social cues has useful emergent group level results such as 1. the synchronisation of patch departure 2. the rapid learning of local habitat depletion 3. the estimation of habitat or bredding colony quality (eg from observation of the number of offspring fledged in various colonies). There are likely to be costs involved in both types of information collection (social and individual) and as a result it may pay to specialise in one or the other. Information pooling among social insects is heavily studied, often in haplodiploid species such as ants or bees.

'''Liu, Y. Passino, K. Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors. ''JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS'' Vol. 115, No. 3, pp. 603–628 (2002)''' [http://www.santafe.edu/events/workshops/images/7/79/Liu_2002_-_Biomimicry_of_Social_Foraging_Bacteria.pdf pdf]

An evolutionary simulation of bacterial social foraging by means of 'attractants' they secrete in space and which others respond to. Extending this with explicit networks might be exciting.

'''Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele et al.'''
[http://www.santafe.edu/events/workshops/images/0/03/Social_network_growth_Catanzaro.pdf]

Using a variant on the “BarabHasi–Albert preferential attachment” model the authors reproduce some of the assortative qualities of social networks. Their variation includes a greater level of mixing as the life of the node is > than that of the edge. It is demonstrated that strong assortativity can break the scale free nature of the networks.
(this could be of interest for the consequences of clustering strategies in the proposed model)

Back to [[games and nets group]]

File:Social network growth Catanzaro.pdf

2006-06-21T17:53:13Z

Greg:

Games and nets literature review

2006-06-21T17:47:38Z

Greg:

Back to [[Games and networks]]

'''Literature'''

'''Eguilez, V. ''et al.'' Cooperation and emergence of role differentiation in the dynamics of social networks. ''arXiv: physics'' (2006) [http://arxiv.org/pdf/physics/0602053 pdf]

I found this paper describing a very similar model and I believe this is more or less what we intend to do.
On this model agents play the PD in a network structure. More or less it goes like this; Links between Defector and defector break and are randomly assigned. Rules (when playing PD) between the agents are adapted by imitating the wealthiest neighbor (this would be adaptation within the agents lifetime (learning), there is no evolutionary adaptation as we discussed in the evening meeting, which we could also implement and compare both).
Their result is some role differentiation between the agents (leaders, conformist, exloiters, etc). Their treating the problem "how the network is dynamically formed or how a given network structure is reached after social agents interact for a long time".

'''Ohtsuki, H., Hauert, C., Lieberman, E. & Nowak, M.A. A simple rule for the evolution of cooperation on graphs and social networks. ''Nature'' 441: 502-505 (2006).''' [http://www.santafe.edu/events/workshops/images/e/e0/OhtsukiEtAl06.pdf pdf]

This is a simple exploration of how network structure -- in particular,
connectedness -- affects the evolution of cooperation. They find that a good
predictor for whether cooperation can invade and spread in a network is whether
the benefit-cost ratio is greater than the (average) degree of the graph. They
derive the result exactly for a cycle, approximately for a random graph where
every node has the same degree, and use simulation to show that the fit is good
for true random graphs and scale-free networks.

'''Santos, F.C., Pacheco, J.M. & Lenaerts T. Evolutionary dynamics of social dilemmas in structured heterogeneous populations. ''Proc Nat Acad Sci USA'' 103: 3490-3494 (2006).''' [http://www.santafe.edu/events/workshops/images/5/58/SantosEtAl06.pdf pdf]

The authors show that heterogeneity in the degree of the graph (e.g. scale-free networks as opposed to single-scale networks) can encourage the evolution of cooperation. They simulate using what amounts to an imitation rule on a fixed network structure, and parameterize the game that is played so that it can represent three popular games: Stag Hunt, Hawk-Dove, and Prisoner's Dilemma.

'''Page, K. Nowak, M. Sigmund, K. The spatial ultimatum game. ''Proc. R. Soc. Lond. B'' 267, 2177-2182 (2000)''' [http://www.santafe.edu/events/workshops/images/8/85/Page_-_spatial_ultimatum_game.pdf pdf]

In an ultimatum game played between members of a population with random mixing offer strategies evolve towards zero, provided the mutation rate per generation is small. On a 1D lattice they approximate a fair split, and on a 2D grid they are around 0.35.

'''Goyal, S. Learning in Networks: a Survey. ''Forthcoming in, Group formation in economics: networks, clubs, and coalitions (2003)'''
[http://www.santafe.edu/events/workshops/images/0/04/Goyal_2003.pdf pdf]

A broad overview of learning on both static and adaptive networks. The paper examines a variety of games including those involving information aquisition, information sharing, cooperation, conflict and others.

'''Jin, E., Girvin, M. and Newman, M. Structure of Growing Social Networks ''Physical Review E (2001)'''
[http://www.santafe.edu/events/workshops/images/1/12/Girvan_and_Newman_2001.pdf pdf]

Some interesting ideas in general, but specifically useful for thinking about how to model the growth and decay of social networks. Also, since this is co-authored by Mark Newman it would be convenient to ask him about the ideas put forth in the paper.

'''Not yet read:

'''Nowak, M. and Sigmund, K. Evolutionary dynamics of biological games. ''Science'' 303 (2004)'''
[http://www.santafe.edu/events/workshops/images/0/0d/Nowak_sigmund_-_evolutionary_dynamics_of_biological_games.pdf pdf]

'''Lieberman, E. Hauert, C. Nowak, M. Evolutionary dynamics on graphs. ''Nature'' 433 (2005)
[http://www.santafe.edu/events/workshops/images/5/58/Lieberman_nowak_sigmund_-_evolutionary_dynamics_on_graphs.pdf pdf]

'''Albert, R. and Barabási, A. Topology of Evolving Networks: Local Events and Universality ''Physical Review Letters'' (2000)'''
[http://www.santafe.edu/events/workshops/images/b/bb/Albert_and_Barabasi_2000.pdf pdf]

'''Jackson, M. and Wolinski, A. A Strategic Model of Social and Economic Networks ''Journal of Economic Theory'' (1996)'''
[http://www.santafe.edu/events/workshops/images/9/9c/Jackson_and_Wolinski_1996.pdf pdf]

'''Bala, V. and Goyal, S. A Noncooperative Model of Network Formation ''Econometrica'' (2000)'''
[http://www.santafe.edu/events/workshops/images/f/f0/Bala_and_Goyal_2000.pdf pdf]

'''Social Foraging

'''Rogers A. Does biology constrain culture? ''American Anthropologist'' 90(4): 819–831 (1988).'''
[http://www.santafe.edu/events/workshops/images/b/b7/Rogers_1988_-_Does_biology_constrain_culture.pdf pdf]

Rogers shows that in a population with both individual learning strategies and social learning strategies, for certain probabilites of environmental change in any given generation, the mixed evolutionarily stable strategy will be at a point at which the payoff from social learning exactly matches that of individual learning. Individual learning is assumed to have a constant, frequency independent payoff. He assumes individual learning to have a cost associated with it and social learning to be costless. The model has no space or other structure across which animals communicate. If the environment changes with too great a probability per generation social learners will be eliminated.

'''Wakano, J. Aoki, K. and Feldman, M. A mathematical analysis of social learning ''Theoretical Population Biology'' 66 249–258 (2004) [http://www.santafe.edu/events/workshops/images/0/0b/Wakano_Aoki_Feldman_2004_-_Evolution_of_Social_Learning%3B_a_mathematical_analysis.pdf pdf]

The authors present a model in which social learning, individual learning and fixed (genetic) strategies are in competition. Social learning has cost ''d'', individual learning has cost ''c'' and making a mistake about the state of the environment has cost ''s''. Costs are ordered ''d < c < s''. The fitnesses of the different strategies vary as a function of the number of generations between environmental changes ''l''. Individual learners win when the environment changes every generation (''l'' = 1), decreasing in frequency as the number of generations between changes increases. Social learners are at zero frequency when ''l'' = 1, rising in frequency while ''l'' < 684. When ''l'' > 684 innate strategies suddenly rise from zero frequency to take over the whole population. This critical value of ''l*'' = 683 is for a given set of parameters .

'''Dall, S. ''et al.'' Information and its use by animals in evolutionary ecology. ''TREE'' 20 4 (2005)'''
[http://www.santafe.edu/events/workshops/images/6/66/Dall_et_al_2005_-_Information_and_its_use_by_animals_in_evolutionary_ecology.pdf pdf]

This paper includes a section on 'inadvertant social information' - ie cues. The authors mention that use of social cues can lead to informational cascades - there's a literature in economics on this that I know exists but haven't read much of. This can be valuable, but can also lead to important errors. An examples among animals is the take-off behaviour of large flocks of birds. Many of the birds in a departing flock will take off on the basis of only social cues from the birds around them - this may be valuable if it usually signifies approaching danger, but a waste of energy if it does not. The sharing of information through social cues has useful emergent group level results such as 1. the synchronisation of patch departure 2. the rapid learning of local habitat depletion 3. the estimation of habitat or bredding colony quality (eg from observation of the number of offspring fledged in various colonies). There are likely to be costs involved in both types of information collection (social and individual) and as a result it may pay to specialise in one or the other. Information pooling among social insects is heavily studied, often in haplodiploid species such as ants or bees.

'''Liu, Y. Passino, K. Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors. ''JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS'' Vol. 115, No. 3, pp. 603–628 (2002)''' [http://www.santafe.edu/events/workshops/images/7/79/Liu_2002_-_Biomimicry_of_Social_Foraging_Bacteria.pdf pdf]

An evolutionary simulation of bacterial social foraging by means of 'attractants' they secrete in space and which others respond to. Extending this with explicit networks might be exciting.

'''Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele et al.'''
[Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele;_Caldarelli,_Guido;_Pietronero,_Luciano..pdf pdf]

Using a variant on the “BarabHasi–Albert preferential attachment” model the authors reproduce some of the assortative qualities of social networks. Their variation includes a greater level of mixing as the life of the node is > than that of the edge. It is demonstrated that strong assortativity can break the scale free nature of the networks.
(this could be of interest for the consequences of clustering strategies in the proposed model)

Back to [[games and nets group]]

Games and nets literature review

2006-06-21T17:46:39Z

Greg:

Back to [[Games and networks]]

'''Literature'''

'''Eguilez, V. ''et al.'' Cooperation and emergence of role differentiation in the dynamics of social networks. ''arXiv: physics'' (2006) [http://arxiv.org/pdf/physics/0602053 pdf]

I found this paper describing a very similar model and I believe this is more or less what we intend to do.
On this model agents play the PD in a network structure. More or less it goes like this; Links between Defector and defector break and are randomly assigned. Rules (when playing PD) between the agents are adapted by imitating the wealthiest neighbor (this would be adaptation within the agents lifetime (learning), there is no evolutionary adaptation as we discussed in the evening meeting, which we could also implement and compare both).
Their result is some role differentiation between the agents (leaders, conformist, exloiters, etc). Their treating the problem "how the network is dynamically formed or how a given network structure is reached after social agents interact for a long time".

'''Ohtsuki, H., Hauert, C., Lieberman, E. & Nowak, M.A. A simple rule for the evolution of cooperation on graphs and social networks. ''Nature'' 441: 502-505 (2006).''' [http://www.santafe.edu/events/workshops/images/e/e0/OhtsukiEtAl06.pdf pdf]

This is a simple exploration of how network structure -- in particular,
connectedness -- affects the evolution of cooperation. They find that a good
predictor for whether cooperation can invade and spread in a network is whether
the benefit-cost ratio is greater than the (average) degree of the graph. They
derive the result exactly for a cycle, approximately for a random graph where
every node has the same degree, and use simulation to show that the fit is good
for true random graphs and scale-free networks.

'''Santos, F.C., Pacheco, J.M. & Lenaerts T. Evolutionary dynamics of social dilemmas in structured heterogeneous populations. ''Proc Nat Acad Sci USA'' 103: 3490-3494 (2006).''' [http://www.santafe.edu/events/workshops/images/5/58/SantosEtAl06.pdf pdf]

The authors show that heterogeneity in the degree of the graph (e.g. scale-free networks as opposed to single-scale networks) can encourage the evolution of cooperation. They simulate using what amounts to an imitation rule on a fixed network structure, and parameterize the game that is played so that it can represent three popular games: Stag Hunt, Hawk-Dove, and Prisoner's Dilemma.

'''Page, K. Nowak, M. Sigmund, K. The spatial ultimatum game. ''Proc. R. Soc. Lond. B'' 267, 2177-2182 (2000)''' [http://www.santafe.edu/events/workshops/images/8/85/Page_-_spatial_ultimatum_game.pdf pdf]

In an ultimatum game played between members of a population with random mixing offer strategies evolve towards zero, provided the mutation rate per generation is small. On a 1D lattice they approximate a fair split, and on a 2D grid they are around 0.35.

'''Goyal, S. Learning in Networks: a Survey. ''Forthcoming in, Group formation in economics: networks, clubs, and coalitions (2003)'''
[http://www.santafe.edu/events/workshops/images/0/04/Goyal_2003.pdf pdf]

A broad overview of learning on both static and adaptive networks. The paper examines a variety of games including those involving information aquisition, information sharing, cooperation, conflict and others.

'''Jin, E., Girvin, M. and Newman, M. Structure of Growing Social Networks ''Physical Review E (2001)'''
[http://www.santafe.edu/events/workshops/images/1/12/Girvan_and_Newman_2001.pdf pdf]

Some interesting ideas in general, but specifically useful for thinking about how to model the growth and decay of social networks. Also, since this is co-authored by Mark Newman it would be convenient to ask him about the ideas put forth in the paper.

'''Not yet read:

'''Nowak, M. and Sigmund, K. Evolutionary dynamics of biological games. ''Science'' 303 (2004)'''
[http://www.santafe.edu/events/workshops/images/0/0d/Nowak_sigmund_-_evolutionary_dynamics_of_biological_games.pdf pdf]

'''Lieberman, E. Hauert, C. Nowak, M. Evolutionary dynamics on graphs. ''Nature'' 433 (2005)
[http://www.santafe.edu/events/workshops/images/5/58/Lieberman_nowak_sigmund_-_evolutionary_dynamics_on_graphs.pdf pdf]

'''Albert, R. and Barabási, A. Topology of Evolving Networks: Local Events and Universality ''Physical Review Letters'' (2000)'''
[http://www.santafe.edu/events/workshops/images/b/bb/Albert_and_Barabasi_2000.pdf pdf]

'''Jackson, M. and Wolinski, A. A Strategic Model of Social and Economic Networks ''Journal of Economic Theory'' (1996)'''
[http://www.santafe.edu/events/workshops/images/9/9c/Jackson_and_Wolinski_1996.pdf pdf]

'''Bala, V. and Goyal, S. A Noncooperative Model of Network Formation ''Econometrica'' (2000)'''
[http://www.santafe.edu/events/workshops/images/f/f0/Bala_and_Goyal_2000.pdf pdf]

'''Social Foraging

'''Rogers A. Does biology constrain culture? ''American Anthropologist'' 90(4): 819–831 (1988).'''
[http://www.santafe.edu/events/workshops/images/b/b7/Rogers_1988_-_Does_biology_constrain_culture.pdf pdf]

Rogers shows that in a population with both individual learning strategies and social learning strategies, for certain probabilites of environmental change in any given generation, the mixed evolutionarily stable strategy will be at a point at which the payoff from social learning exactly matches that of individual learning. Individual learning is assumed to have a constant, frequency independent payoff. He assumes individual learning to have a cost associated with it and social learning to be costless. The model has no space or other structure across which animals communicate. If the environment changes with too great a probability per generation social learners will be eliminated.

'''Wakano, J. Aoki, K. and Feldman, M. A mathematical analysis of social learning ''Theoretical Population Biology'' 66 249–258 (2004) [http://www.santafe.edu/events/workshops/images/0/0b/Wakano_Aoki_Feldman_2004_-_Evolution_of_Social_Learning%3B_a_mathematical_analysis.pdf pdf]

The authors present a model in which social learning, individual learning and fixed (genetic) strategies are in competition. Social learning has cost ''d'', individual learning has cost ''c'' and making a mistake about the state of the environment has cost ''s''. Costs are ordered ''d < c < s''. The fitnesses of the different strategies vary as a function of the number of generations between environmental changes ''l''. Individual learners win when the environment changes every generation (''l'' = 1), decreasing in frequency as the number of generations between changes increases. Social learners are at zero frequency when ''l'' = 1, rising in frequency while ''l'' < 684. When ''l'' > 684 innate strategies suddenly rise from zero frequency to take over the whole population. This critical value of ''l*'' = 683 is for a given set of parameters .

'''Dall, S. ''et al.'' Information and its use by animals in evolutionary ecology. ''TREE'' 20 4 (2005)'''
[http://www.santafe.edu/events/workshops/images/6/66/Dall_et_al_2005_-_Information_and_its_use_by_animals_in_evolutionary_ecology.pdf pdf]

This paper includes a section on 'inadvertant social information' - ie cues. The authors mention that use of social cues can lead to informational cascades - there's a literature in economics on this that I know exists but haven't read much of. This can be valuable, but can also lead to important errors. An examples among animals is the take-off behaviour of large flocks of birds. Many of the birds in a departing flock will take off on the basis of only social cues from the birds around them - this may be valuable if it usually signifies approaching danger, but a waste of energy if it does not. The sharing of information through social cues has useful emergent group level results such as 1. the synchronisation of patch departure 2. the rapid learning of local habitat depletion 3. the estimation of habitat or bredding colony quality (eg from observation of the number of offspring fledged in various colonies). There are likely to be costs involved in both types of information collection (social and individual) and as a result it may pay to specialise in one or the other. Information pooling among social insects is heavily studied, often in haplodiploid species such as ants or bees.

'''Liu, Y. Passino, K. Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors. ''JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS'' Vol. 115, No. 3, pp. 603–628 (2002)''' [http://www.santafe.edu/events/workshops/images/7/79/Liu_2002_-_Biomimicry_of_Social_Foraging_Bacteria.pdf pdf]

An evolutionary simulation of bacterial social foraging by means of 'attractants' they secrete in space and which others respond to. Extending this with explicit networks might be exciting.

'''Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele et al.'''
["Social_network_growth_with_assortative_mixing._Physica_A_338,_119_(2004)._Catanzaro,_Michele;_Caldarelli,_Guido;_Pietronero,_Luciano..pdf pdf]

Using a variant on the “BarabHasi–Albert preferential attachment” model the authors reproduce some of the assortative qualities of social networks. Their variation includes a greater level of mixing as the life of the node is > than that of the edge. It is demonstrated that strong assortativity can break the scale free nature of the networks.
(this could be of interest for the consequences of clustering strategies in the proposed model)

Back to [[games and nets group]]

File:Social network growth with assortative mixing. Physica A 338, 119 (2004). Catanzaro, Michele; Caldarelli, Guido; Pietronero, Luciano..pdf

2006-06-21T17:42:30Z

Greg:

CSSS 2006 Santa Fe-Participants

2006-06-16T05:01:08Z

Greg:

{{CSSS 2006--Santa Fe}}
[[Katharine Anderson]] 
University of Michigan, Ann Arbor, MI 
email: andersok (at) umich (dot) edu 
Suite 2 #6 

[[Sandra Arndt]] 
Universiteit Utrecht, The Netherlands 
email: arndt (at) geo (dot) uu (dot) nl 
room ext: 4307 
Sunflower 8 

[[Stefan Braunewell]] 
University of Bremen, Germany 
Calliope 10A 
room ext: 4155

[[William Burnside]] 
University of New Mexico, Albuquerque, NM

[[Mike Butters]] 
Nativis, San Diego, CA

[[Juan Calderon]] 
email: ju-cald1 (at) uniandes (dot) edu (dot) co 
room ext: 4157 
Calliope 12 
Universidad de los Andes, Bogota, Colombia 
[http://www.dumpa.tk Home page]

[[Fabrice Cavarretta]] - Calliope 13 ext. 4158 
INSEAD, Fontainebleau, France 
Email: Fabrice.Cavarretta(@)insead.edu Mob:+33 6 09 59 46 74 
MSNM: fabrice@cavarretta.com AIM/YM: fcaspam Skype: fcavarretta 
Web: [http://ot.cavarretta.com ot.cavarretta.com] 

[[Brian Chapados]] 
The Scripps Research Institute, La Jolla, CA

[[Basit Chaudhry]] 
UCLA/RAND, Los Angeles, CA
email: basitchaudhry(at)yahoo.com 
mobile: 310 359 3729 
Calliope rm 15 

[[Arturo Chavoya]]- Polyhymnia 25 Ext.4230 
Universite de Toulouse I, France 
Email & MSNM: achavoya AT hotmail DOT com

[[Adrian de Froment]] Calliope 15a, ext 4161 
Princeton University, NJ 
Email: adriande at princeton dot edu; Phone: 609 933 3177 
MSN: adriandefroment at hotmail dot com; AIM: adriandefrom 

[[Matina Donaldson]] 
University of Washington, Seattle, WA 
Email: donaldso at eva dot mpg dot de 
Mobile: (206) 403-6182 
Location: Suite 2, Room 10

[[Haifeng Du]] 
Morrison Institute for Population and Resource Studies, Stanford, CA

[[Johan Elkink]] 
Trinity College, Dublin, Ireland 
All details can be found here: [http://jaeweb.cantr.net]

[[Dietrich Falkenthal]] 
MITRE

[[Sebastian Fallert]] 
University of Cambridge, UK

[[Anna Fedor]] 
Eötvös Lorán University of Sciences, Budapest, Hungary

[[Alessandro Gagliardi]] - Calliope 22 
Rutgers University, Newark, NJ 
Tel: 917.805.9797 
Email: alessandro [at] gagliardi [dot] name 
AIM: soleklypse

[[Sam Garg]] 
Stanford University, Stanford, CA

[[Harry Halpin]] 
University of Edinburgh, Scotland

[[Douglas Hoskins]] 
Boeing, Seattle, WA

[[Izzat Jarudi]] 
Yale University, New Haven, CT 
izzat.jarudi at yale dot edu

[[Elham Kashefi]] 
Institute for Quantum Computing, Waterloo, Ontario, Canada

[[Nikhil Kaza]] 
University of Illinois at Urbana-Champaign, IL 
nkaza (AT) UIUC (doT) edu 217 419 4232(c)
Calliope 26 - extn. 4172

[[Heinz Koeppl]] 
University of California, Berkeley, CA

[[Cornelia Kreutzer]] 
University of Limerick, Limerick, Ireland

[[Lukas Kroc]] 
Cornell University, Ithaca, NY 
email: kroc at cs dot cornell dot edu 
cell: 607-342-5267 
SJC campus: suite 1, room 4

[[Jonathan Lafky]] 
University of Pittsburgh, PA 
email address backwards: moc.liamg@ykfalj 
Cell: four one two 849 719five 
Suite 1, room 5.

[[Elizabeth Leicht]] 
University of Michigan, Ann Arbor, MI 
email: eleicht at umich dot (standard academic ending) 
cell: 734-triple two-753 one

[[Tamas Makany]] 
University of Southampton, Hampshire, UK

[[Michael Makowsky]] 
George Mason University, Falls Church, VA
Urania, room 16a
email: mmakowsk(at)gmu.edu

[[Christopher Marton]] - Polyhymnia 11 A&B ext.4216 
Massachusetts Institute of Technology, Cambridge, MA 
email: cmarton at mit dot edu

[[Greg McInerny]] 
Polyhymnia 12, St Johns. EXT 4217. 
University of Leeds/The Centre for Ecology and Hydrology, Banchory, Leeds, UK

[[Patrick Meier]] 
The Fletcher School, Boston MA 
Email: Patrick.Meier(@)Tufts.edu; Cell:+1 646-361-2645 
Skype ID: patrickmeierskype 
Web: [http://fletcher.tufts.edu/phd/students/Meier.html PhD Profile and Research ] 

[[Charlie Messina]] 
Pioneer Hi-Bred International, Johnston, IA

[[Javier Muñoz García]] 
Universidad Carlos III de Madrid, Leganés, Madrid, Spain 
Location on campus: Polyhymnia 14; Phone (505) 995-4219 
Email: jamunoz*AT*math.uc3m.es; messenger:javiermunozgarcia*AT*hotmail.com

[[Andreea Munteanu]] 
Universitat Pompeu Fabra, Barcelona, Spain 
Location on campus: Suite 2, room 3, phone (505) 995-4303 
Email: andreea.munteanu(AT)upf.edu

[[Christoph Neugebauer]] 
University of Cambridge, UK 
Location on campus: Polyhymnia 15, ext. 4220 
email: cjn24 AT cam.ac.uk

[[Paul Newton]] 
Boeing, Seattle, WA

[[Linsey O'Brien]] 
MITRE, Bedford, MA

[[Michael Raghib Moreno]] 
Princeton University, NJ 
Polyhymnia 16, (505) 995 4221 
mraghib at math at princeton dot edu

[[Valentin Robu]] 
CWI, Dutch Research Center for Mathematics and Computer Science, Amsterdam, The Netherlands
Email: robu at cwi dot nl 
Location on campus: Polyhymnia 16A

[[David Rojas]] 
NASA, Hampton, VA

[[Akiko Satake]] 
Princeton University, NJ

[[David Schaefer]] 
Arizona State University, Tempe, AZ 
Email: david dot schaefer at asu dot edu 
Location on campus: Polyhymnia 26

[[Susanne Schindler]] 
Max Planck Institute, Leipzig, Germany

[[Jie Shao]] 
University of Oklahoma, Norman, OK

[[Hana Shepherd]] 
Princeton University, NJ 
On campus: Suite 5, room 2, ext. 4330 
hshepher [at] princeton [dot] edu 
303 859-7238 

[[Tetsuya Shoji]] 
Toyota Motor Corporation, Japan

[[Andrew Stout]] 
U. Massachusetts - Amherst, Sunderland, MA

[[Andrea Tanzer]] 
University of Vienna, Austria 
email: at@tbi.univie.ac.at 
location on campus: suite 5, room 3, phone (505) 995-4331 
skype: atanzer

[[Jorge Tavares]] 
University of Coimbra, Portugal 
jast [at] dei [dot] uc [dot] pt 
Polyhymnia, room 21, (505) 995-4225

[[Marko Thaler]] 
University of Ljubljana, Slovenia

[[Brian Tivnan]] 
MITRE, McLean, VA

[[Spandan Tiwari]] 
University of Missouri-Rolla Rolla, MI

[[Maria Vivien Visaya]] 
Kyoto University, Japan

[[Jack Waddell]] 
University of Michigan, Ann Arbor, MI

[[Saskia Werners]] 
Wageningen University and Research Centre, Amsterdam, The Netherlands
room 5 in D5 (building 41). ext 4333
E: saskia -at- mungo.nl

[[Ryan Woodard]] 
British Antarctic Survey, Cambridge, UK

CSSS 2006 Santa Fe-Participants

2006-06-16T04:59:32Z

Greg:

{{CSSS 2006--Santa Fe}}
[[Katharine Anderson]] 
University of Michigan, Ann Arbor, MI 
email: andersok (at) umich (dot) edu 
Suite 2 #6 

[[Sandra Arndt]] 
Universiteit Utrecht, The Netherlands 
email: arndt (at) geo (dot) uu (dot) nl 
room ext: 4307 
Sunflower 8 

[[Stefan Braunewell]] 
University of Bremen, Germany 
Calliope 10A 
room ext: 4155

[[William Burnside]] 
University of New Mexico, Albuquerque, NM

[[Mike Butters]] 
Nativis, San Diego, CA

[[Juan Calderon]] 
email: ju-cald1 (at) uniandes (dot) edu (dot) co 
room ext: 4157 
Calliope 12 
Universidad de los Andes, Bogota, Colombia 
[http://www.dumpa.tk Home page]

[[Fabrice Cavarretta]] - Calliope 13 ext. 4158 
INSEAD, Fontainebleau, France 
Email: Fabrice.Cavarretta(@)insead.edu Mob:+33 6 09 59 46 74 
MSNM: fabrice@cavarretta.com AIM/YM: fcaspam Skype: fcavarretta 
Web: [http://ot.cavarretta.com ot.cavarretta.com] 

[[Brian Chapados]] 
The Scripps Research Institute, La Jolla, CA

[[Basit Chaudhry]] 
UCLA/RAND, Los Angeles, CA
email: basitchaudhry(at)yahoo.com 
mobile: 310 359 3729 
Calliope rm 15 

[[Arturo Chavoya]]- Polyhymnia 25 Ext.4230 
Universite de Toulouse I, France 
Email & MSNM: achavoya AT hotmail DOT com

[[Adrian de Froment]] Calliope 15a, ext 4161 
Princeton University, NJ 
Email: adriande at princeton dot edu; Phone: 609 933 3177 
MSN: adriandefroment at hotmail dot com; AIM: adriandefrom 

[[Matina Donaldson]] 
University of Washington, Seattle, WA 
Email: donaldso at eva dot mpg dot de 
Mobile: (206) 403-6182 
Location: Suite 2, Room 10

[[Haifeng Du]] 
Morrison Institute for Population and Resource Studies, Stanford, CA

[[Johan Elkink]] 
Trinity College, Dublin, Ireland 
All details can be found here: [http://jaeweb.cantr.net]

[[Dietrich Falkenthal]] 
MITRE

[[Sebastian Fallert]] 
University of Cambridge, UK

[[Anna Fedor]] 
Eötvös Lorán University of Sciences, Budapest, Hungary

[[Alessandro Gagliardi]] - Calliope 22 
Rutgers University, Newark, NJ 
Tel: 917.805.9797 
Email: alessandro [at] gagliardi [dot] name 
AIM: soleklypse

[[Sam Garg]] 
Stanford University, Stanford, CA

[[Harry Halpin]] 
University of Edinburgh, Scotland

[[Douglas Hoskins]] 
Boeing, Seattle, WA

[[Izzat Jarudi]] 
Yale University, New Haven, CT 
izzat.jarudi at yale dot edu

[[Elham Kashefi]] 
Institute for Quantum Computing, Waterloo, Ontario, Canada

[[Nikhil Kaza]] 
University of Illinois at Urbana-Champaign, IL 
nkaza (AT) UIUC (doT) edu 217 419 4232(c)
Calliope 26 - extn. 4172

[[Heinz Koeppl]] 
University of California, Berkeley, CA

[[Cornelia Kreutzer]] 
University of Limerick, Limerick, Ireland

[[Lukas Kroc]] 
Cornell University, Ithaca, NY 
email: kroc at cs dot cornell dot edu 
cell: 607-342-5267 
SJC campus: suite 1, room 4

[[Jonathan Lafky]] 
University of Pittsburgh, PA 
email address backwards: moc.liamg@ykfalj 
Cell: four one two 849 719five 
Suite 1, room 5.

[[Elizabeth Leicht]] 
University of Michigan, Ann Arbor, MI 
email: eleicht at umich dot (standard academic ending) 
cell: 734-triple two-753 one

[[Tamas Makany]] 
University of Southampton, Hampshire, UK

[[Michael Makowsky]] 
George Mason University, Falls Church, VA
Urania, room 16a
email: mmakowsk(at)gmu.edu

[[Christopher Marton]] - Polyhymnia 11 A&B ext.4216 
Massachusetts Institute of Technology, Cambridge, MA 
email: cmarton at mit dot edu

[[Greg McInerny]] 
Polyhymnia 12, St Johns />
University of Leeds/The Centre for Ecology and Hydrology, Banchory, Leeds, UK

[[Patrick Meier]] 
The Fletcher School, Boston MA 
Email: Patrick.Meier(@)Tufts.edu; Cell:+1 646-361-2645 
Skype ID: patrickmeierskype 
Web: [http://fletcher.tufts.edu/phd/students/Meier.html PhD Profile and Research ] 

[[Charlie Messina]] 
Pioneer Hi-Bred International, Johnston, IA

[[Javier Muñoz García]] 
Universidad Carlos III de Madrid, Leganés, Madrid, Spain 
Location on campus: Polyhymnia 14; Phone (505) 995-4219 
Email: jamunoz*AT*math.uc3m.es; messenger:javiermunozgarcia*AT*hotmail.com

[[Andreea Munteanu]] 
Universitat Pompeu Fabra, Barcelona, Spain 
Location on campus: Suite 2, room 3, phone (505) 995-4303 
Email: andreea.munteanu(AT)upf.edu

[[Christoph Neugebauer]] 
University of Cambridge, UK 
Location on campus: Polyhymnia 15, ext. 4220 
email: cjn24 AT cam.ac.uk

[[Paul Newton]] 
Boeing, Seattle, WA

[[Linsey O'Brien]] 
MITRE, Bedford, MA

[[Michael Raghib Moreno]] 
Princeton University, NJ 
Polyhymnia 16, (505) 995 4221 
mraghib at math at princeton dot edu

[[Valentin Robu]] 
CWI, Dutch Research Center for Mathematics and Computer Science, Amsterdam, The Netherlands
Email: robu at cwi dot nl 
Location on campus: Polyhymnia 16A

[[David Rojas]] 
NASA, Hampton, VA

[[Akiko Satake]] 
Princeton University, NJ

[[David Schaefer]] 
Arizona State University, Tempe, AZ 
Email: david dot schaefer at asu dot edu 
Location on campus: Polyhymnia 26

[[Susanne Schindler]] 
Max Planck Institute, Leipzig, Germany

[[Jie Shao]] 
University of Oklahoma, Norman, OK

[[Hana Shepherd]] 
Princeton University, NJ 
On campus: Suite 5, room 2, ext. 4330 
hshepher [at] princeton [dot] edu 
303 859-7238 

[[Tetsuya Shoji]] 
Toyota Motor Corporation, Japan

[[Andrew Stout]] 
U. Massachusetts - Amherst, Sunderland, MA

[[Andrea Tanzer]] 
University of Vienna, Austria 
email: at@tbi.univie.ac.at 
location on campus: suite 5, room 3, phone (505) 995-4331 
skype: atanzer

[[Jorge Tavares]] 
University of Coimbra, Portugal 
jast [at] dei [dot] uc [dot] pt 
Polyhymnia, room 21, (505) 995-4225

[[Marko Thaler]] 
University of Ljubljana, Slovenia

[[Brian Tivnan]] 
MITRE, McLean, VA

[[Spandan Tiwari]] 
University of Missouri-Rolla Rolla, MI

[[Maria Vivien Visaya]] 
Kyoto University, Japan

[[Jack Waddell]] 
University of Michigan, Ann Arbor, MI

[[Saskia Werners]] 
Wageningen University and Research Centre, Amsterdam, The Netherlands
room 5 in D5 (building 41). ext 4333
E: saskia -at- mungo.nl

[[Ryan Woodard]] 
British Antarctic Survey, Cambridge, UK

CSSS 2006 Santa Fe-Participants

2006-06-16T04:58:38Z

Greg:

{{CSSS 2006--Santa Fe}}
[[Katharine Anderson]] 
University of Michigan, Ann Arbor, MI 
email: andersok (at) umich (dot) edu 
Suite 2 #6 

[[Sandra Arndt]] 
Universiteit Utrecht, The Netherlands 
email: arndt (at) geo (dot) uu (dot) nl 
room ext: 4307 
Sunflower 8 

[[Stefan Braunewell]] 
University of Bremen, Germany 
Calliope 10A 
room ext: 4155

[[William Burnside]] 
University of New Mexico, Albuquerque, NM

[[Mike Butters]] 
Nativis, San Diego, CA

[[Juan Calderon]] 
email: ju-cald1 (at) uniandes (dot) edu (dot) co 
room ext: 4157 
Calliope 12 
Universidad de los Andes, Bogota, Colombia 
[http://www.dumpa.tk Home page]

[[Fabrice Cavarretta]] - Calliope 13 ext. 4158 
INSEAD, Fontainebleau, France 
Email: Fabrice.Cavarretta(@)insead.edu Mob:+33 6 09 59 46 74 
MSNM: fabrice@cavarretta.com AIM/YM: fcaspam Skype: fcavarretta 
Web: [http://ot.cavarretta.com ot.cavarretta.com] 

[[Brian Chapados]] 
The Scripps Research Institute, La Jolla, CA

[[Basit Chaudhry]] 
UCLA/RAND, Los Angeles, CA
email: basitchaudhry(at)yahoo.com 
mobile: 310 359 3729 
Calliope rm 15 

[[Arturo Chavoya]]- Polyhymnia 25 Ext.4230 
Universite de Toulouse I, France 
Email & MSNM: achavoya AT hotmail DOT com

[[Adrian de Froment]] Calliope 15a, ext 4161 
Princeton University, NJ 
Email: adriande at princeton dot edu; Phone: 609 933 3177 
MSN: adriandefroment at hotmail dot com; AIM: adriandefrom 

[[Matina Donaldson]] 
University of Washington, Seattle, WA 
Email: donaldso at eva dot mpg dot de 
Mobile: (206) 403-6182 
Location: Suite 2, Room 10

[[Haifeng Du]] 
Morrison Institute for Population and Resource Studies, Stanford, CA

[[Johan Elkink]] 
Trinity College, Dublin, Ireland 
All details can be found here: [http://jaeweb.cantr.net]

[[Dietrich Falkenthal]] 
MITRE

[[Sebastian Fallert]] 
University of Cambridge, UK

[[Anna Fedor]] 
Eötvös Lorán University of Sciences, Budapest, Hungary

[[Alessandro Gagliardi]] - Calliope 22 
Rutgers University, Newark, NJ 
Tel: 917.805.9797 
Email: alessandro [at] gagliardi [dot] name 
AIM: soleklypse

[[Sam Garg]] 
Stanford University, Stanford, CA

[[Harry Halpin]] 
University of Edinburgh, Scotland

[[Douglas Hoskins]] 
Boeing, Seattle, WA

[[Izzat Jarudi]] 
Yale University, New Haven, CT 
izzat.jarudi at yale dot edu

[[Elham Kashefi]] 
Institute for Quantum Computing, Waterloo, Ontario, Canada

[[Nikhil Kaza]] 
University of Illinois at Urbana-Champaign, IL 
nkaza (AT) UIUC (doT) edu 217 419 4232(c)
Calliope 26 - extn. 4172

[[Heinz Koeppl]] 
University of California, Berkeley, CA

[[Cornelia Kreutzer]] 
University of Limerick, Limerick, Ireland

[[Lukas Kroc]] 
Cornell University, Ithaca, NY 
email: kroc at cs dot cornell dot edu 
cell: 607-342-5267 
SJC campus: suite 1, room 4

[[Jonathan Lafky]] 
University of Pittsburgh, PA 
email address backwards: moc.liamg@ykfalj 
Cell: four one two 849 719five 
Suite 1, room 5.

[[Elizabeth Leicht]] 
University of Michigan, Ann Arbor, MI 
email: eleicht at umich dot (standard academic ending) 
cell: 734-triple two-753 one

[[Tamas Makany]] 
University of Southampton, Hampshire, UK

[[Michael Makowsky]] 
George Mason University, Falls Church, VA
Urania, room 16a
email: mmakowsk(at)gmu.edu

[[Christopher Marton]] - Polyhymnia 11 A&B ext.4216 
Massachusetts Institute of Technology, Cambridge, MA 
email: cmarton at mit dot edu

[[Greg McInerny]] 
Polyhymnia 12
University of Leeds/The Centre for Ecology and Hydrology, Banchory, Leeds, UK

[[Patrick Meier]] 
The Fletcher School, Boston MA 
Email: Patrick.Meier(@)Tufts.edu; Cell:+1 646-361-2645 
Skype ID: patrickmeierskype 
Web: [http://fletcher.tufts.edu/phd/students/Meier.html PhD Profile and Research ] 

[[Charlie Messina]] 
Pioneer Hi-Bred International, Johnston, IA

[[Javier Muñoz García]] 
Universidad Carlos III de Madrid, Leganés, Madrid, Spain 
Location on campus: Polyhymnia 14; Phone (505) 995-4219 
Email: jamunoz*AT*math.uc3m.es; messenger:javiermunozgarcia*AT*hotmail.com

[[Andreea Munteanu]] 
Universitat Pompeu Fabra, Barcelona, Spain 
Location on campus: Suite 2, room 3, phone (505) 995-4303 
Email: andreea.munteanu(AT)upf.edu

[[Christoph Neugebauer]] 
University of Cambridge, UK 
Location on campus: Polyhymnia 15, ext. 4220 
email: cjn24 AT cam.ac.uk

[[Paul Newton]] 
Boeing, Seattle, WA

[[Linsey O'Brien]] 
MITRE, Bedford, MA

[[Michael Raghib Moreno]] 
Princeton University, NJ 
Polyhymnia 16, (505) 995 4221 
mraghib at math at princeton dot edu

[[Valentin Robu]] 
CWI, Dutch Research Center for Mathematics and Computer Science, Amsterdam, The Netherlands
Email: robu at cwi dot nl 
Location on campus: Polyhymnia 16A

[[David Rojas]] 
NASA, Hampton, VA

[[Akiko Satake]] 
Princeton University, NJ

[[David Schaefer]] 
Arizona State University, Tempe, AZ 
Email: david dot schaefer at asu dot edu 
Location on campus: Polyhymnia 26

[[Susanne Schindler]] 
Max Planck Institute, Leipzig, Germany

[[Jie Shao]] 
University of Oklahoma, Norman, OK

[[Hana Shepherd]] 
Princeton University, NJ 
On campus: Suite 5, room 2, ext. 4330 
hshepher [at] princeton [dot] edu 
303 859-7238 

[[Tetsuya Shoji]] 
Toyota Motor Corporation, Japan

[[Andrew Stout]] 
U. Massachusetts - Amherst, Sunderland, MA

[[Andrea Tanzer]] 
University of Vienna, Austria 
email: at@tbi.univie.ac.at 
location on campus: suite 5, room 3, phone (505) 995-4331 
skype: atanzer

[[Jorge Tavares]] 
University of Coimbra, Portugal 
jast [at] dei [dot] uc [dot] pt 
Polyhymnia, room 21, (505) 995-4225

[[Marko Thaler]] 
University of Ljubljana, Slovenia

[[Brian Tivnan]] 
MITRE, McLean, VA

[[Spandan Tiwari]] 
University of Missouri-Rolla Rolla, MI

[[Maria Vivien Visaya]] 
Kyoto University, Japan

[[Jack Waddell]] 
University of Michigan, Ann Arbor, MI

[[Saskia Werners]] 
Wageningen University and Research Centre, Amsterdam, The Netherlands
room 5 in D5 (building 41). ext 4333
E: saskia -at- mungo.nl

[[Ryan Woodard]] 
British Antarctic Survey, Cambridge, UK

Greg McInerny

2006-04-28T10:36:20Z

Greg:

I am in the Second year of my PhD at the [http://www.ceh.ac.uk The Centre for Ecology and Hydrology, Banchory] and the [http://www.fbs.leeds.ac.uk University of Leeds.]

[[Image:Photo-0531.jpg]]

Using experimental microcosms (the soil mite ''Sancassania berlesei'') and simulation models, I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:

•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.

•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.

•How scale differences between processes may impact these responses to change.

•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

'''Answers to Dan's questions.....'''

What topics do you have some expertise in and would you be willing to help others learn them?

''Ecology and evolution.''

What do you want to learn?

''I would like to learn some new skills for the investigation of dynamical systems occurring on networks, but it’s quite likely I will be side tracked on a personal novelty.''

''Also some exposure to more multidisciplinary subjects, (social networks, molecular biology, evolution in other systems), introduce food web ecology (evolution of ecosystems) and epidemiology into my research, improve my mathematics and programming; more team working skills are always on the list….''

''Basically lots.''

Do you have any projects that would benefit from interdisciplinary approach?

''Most probably more than I think. My interests in the context dependent interactions between environmental landscapes and ecological and evolutionary processes may have considerable analogies with problems in economics, computing and other network related systems.''

Do you have any ideas for what sort of project you would like to attack this summer?

''I have a number of things I’m interested in doing at the moment relating to the evolutionary consequences of ecological dynamics and their feedback. However I’d be keen to tackle a problem that is outside of my research area or arises from an idea in the summer school.''

What's your favorite "big problem"?

''The interaction between landscapes and agents, and their reciprocal evolution.''

If you were given the opportunity to see where we were in one hundred years with respect to progress on one problem/subject, what would it be?

''Evolution of social strategies in an increasing population.''

Greg McInerny

2006-04-05T12:22:12Z

Greg:

Greg McInerny

2006-04-05T12:20:45Z

Greg:

I am in the Second year of my PhD at the [http://www.ceh.ac.uk The Centre for Ecology and Hydrology, Banchory] and the [http://www.fbs.leeds.ac.uk University of Leeds].

[[Image:Photo-0531.jpg]]

Using experimental microcosms (the soil mite ''Sancassania berlesei'') and simulation models, I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:

•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.

•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.

•How scale differences between processes may impact these responses to change.

•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

Greg McInerny

2006-04-05T12:17:08Z

Greg:

I am in the Second year of my PhD at the [http://www.ceh.ac.uk The Centre for Ecology and Hydrology, Banchory] and the [http://www.fbs.leeds.ac.uk Univeristy of Leeds].

[[Image:Photo-0531.jpg]]

Using experimental microcosms (the soil mite ''Sancassania berlesei'') and simulation models, I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:

•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.

•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.

•How scale differences between processes may impact these responses to change.

•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

Greg McInerny

2006-04-05T12:15:26Z

Greg:

I am in the Second year of my PhD at the Centre for Ecology and Hydrology, Banchory [http://www.ceh.ac.uk The Centre for Ecology and Hydrology, Banchory] and the [http://www.fbs.leeds.ac.uk Univeristy of Leeds].

[[Image:Photo-0531.jpg]]

Using experimental microcosms (soil mites) and simulation models (C++), I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:

•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.

•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.

•How scale differences between processes may impact these responses to change.

•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

Greg McInerny

2006-04-05T12:11:41Z

Greg:

I am in the Second year of my PhD at the Centre for Ecology and Hydrology, Banchory (www.ceh.ac.uk) and the University of Leeds (www.fbs.leeds.ac.uk).
[[Image:Photo-0531.jpg]]
Using experimental microcosms (soil mites) and simulation models (C++), I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:
•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.
•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.
•How scale differences between processes may impact these responses to change.
•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

Greg McInerny

2006-04-05T12:10:36Z

Greg:

I am in the Second year of my PhD at the Centre for Ecology and Hydrology, Banchory (www.ceh.ac.uk) and the University of Leeds (www.fbs.leeds.ac.uk).
[[Photo-0531.jpg]]
Using experimental microcosms (soil mites) and simulation models (C++), I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:
•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.
•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.
•How scale differences between processes may impact these responses to change.
•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

File:Photo-0531.jpg

2006-04-05T12:08:43Z

Greg:

Greg McInerny

2006-04-05T12:07:57Z

Greg:

I am in the Second year of my PhD at the Centre for Ecology and Hydrology, Banchory ([www.ceh.ac.uk]) and the University of Leeds ([www.fbs.leeds.ac.uk]).
[[Photo-531.jpg]]
Using experimental microcosms (soil mites) and simulation models (C++), I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:
•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.
•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.
•How scale differences between processes may impact these responses to change.
•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

Greg McInerny

2006-04-05T12:06:30Z

Greg:

I am in the Second year of my PhD at the Centre for Ecology and Hydrology, Banchory (www.ceh.ac.uk) and the University of Leeds (www.fbs.leeds.ac.uk).
[[Photo-531.jpg]]
Using experimental microcosms (soil mites) and simulation models (C++), I am investigating how ecological and evolutionary processes, and their interaction, are affected by environmental change and spatial structuring.
In particular my studies focus on:
•How the scale and type of spatial patterning in the environment interacts with individual, population and intra-specific processes to shape population structure.
•The impact of population structure on ecological and evolutionary processes that determine responses to perturbation and environmental change.
•How scale differences between processes may impact these responses to change.
•The power of dispersal in assorting population variation and its impact on projecting responses to a period of environmental change.

File:Photo-531.jpg

2006-04-05T11:56:33Z

Greg: