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Barry Wellman
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S.D. Clark Professor of Sociology, FRSC NetLab Director
Department of Sociology 725 Spadina Avenue, Room 388
University of Toronto Toronto Canada M5S 2J4 twitter:barrywellman
http://www.chass.utoronto.ca/~wellman fax:+1-416-978-3963
Updating history: http://chass.utoronto.ca/oldnew/cybertimes.php
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Cooperation through imitation and exclusion in networks , Journal of
Economic Dynamics and Control
abstract: We study the coevolution of networks and action choices in a
Prisoners' Dilemma. Agents in our model learn about both action choices
and choices of interaction partners (links) by imitating successful
behavior of others. The resulting dynamics yields outcomes where both
cooperators and defectors coexist under a wide range of parameters. Two
scenarios can arise. Either there is full separation of defectors and
cooperators, i.e. they are found in two different, disconnected
components. Or there is marginalization of defectors, i.e. connected
networks emerge with a center of cooperators and a periphery of defectors.
* [28] Cooperation through imitation and exclusion in networks, Fosco C ,
Mengel F, December 2010, DOI: 10.1016/j.jedc.2010.12.002, Journal of
Economic Dynamics and Control, in Press
[28] http://dx.doi.org/10.1016/j.jedc.2010.12.002
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13.01. Models of coalition or alliance formation , Journal of Theoretical
Biology
Abstract: More than half a century has now elapsed since coalition or
alliance formation theory (CAFT) was first developed. During that time,
researchers have amassed a vast amount of detailed and high-quality data
on coalitions or alliances among primates and other animals. But models
have not kept pace, and more relevant theory is needed. In particular,
even though CAFT is primarily an exercise in polyadic game theory, game
theorists have devoted relatively little attention to questions that
motivate field research, and much remains largely unexplored. The state of
the art is both a challenge and an opportunity. In this review we describe
a variety of game-theoretic and related modelling approaches that have
much untapped potential to address the questions that field biologists
ask.
* [30] Models of coalition or alliance formation, Mesterton-Gibbons M ,
Gavrilets S , Gravner J , Akçay E, December 2010, DOI:
10.1016/j.jtbi.2010.12.031, Journal of Theoretical Biology, in Press
* Contributed by [31] Segismundo
[30] http://dx.doi.org/10.1016/j.jtbi.2010.12.031
[31] http://segis.name
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18. New System for Analyzing Information on WikiLeaks, Social Media ,
ScienceDaily
Excerpts: () has designed a system for exploring information on networks
or graphs that can complement internet search engines and is of particular
interest in areas related to social media, the internet, biomedicine,
fraud detection, education and advanced bibliographic searches. () the
technology can be used to extract information from WikiLeaks from two
perspectives: one, to obtain generic indicators that provide information
on whether the data network has the features of a social network and
whether communities of data are created that can provide relevant
information; and two, to use the documents hosted on the website to
analyze how a topic evolves over time, ().
* [38] New System for Analyzing Information on WikiLeaks, Social Media,
2011/01/04, ScienceDaily & Universitat Politcnica de Catalunya
[38] http://www.sciencedaily.com/releases/2011/01/110103110152.htm
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19.03. Introduction to Complexity and Complex Systems , CRC Press
Summary: The boundaries between simple and complicated, and complicated
and complex system designations are fuzzy and debatable, even using
quantitative measures of complexity. However, if you are a biomedical
engineer, a biologist, physiologist, economist, politician, stock market
speculator, or politician, you have encountered complex systems.
Furthermore, your success depends on your ability to successfully interact
with and manage a variety of complex systems. In order not to be
blindsided by unexpected results, we need a systematic, comprehensive way
of analyzing, modeling, and simulating complex systems to predict
non-anticipated outcomes. (...)
* [43] Introduction to Complexity and Complex Systems, Robert B. Northrop,
2010/12/08, CRC Press
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19.04. Chaos: The Science of Predictable Random Motion , Oxford University
Press
Summary: Based on only elementary mathematics, this engaging account of
chaos theory bridges the gap between introductions for the layman and
college-level texts. It develops the science of dynamics in terms of small
time steps, describes the phenomenon of chaos through simple examples, and
concludes with a close look at a homoclinic tangle, the mathematical
monster at the heart of chaos. The presentation is enhanced by many
figures, animations of chaotic motion (available on a companion CD), and
biographical sketches of the pioneers of dynamics and chaos theory. (...)
* [45] Chaos: The Science of Predictable Random Motion, Richard Kautz,
2010/12/30, Oxford University Press
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19.05. Networks of the Brain , The MIT Press
Summary: Over the last decade, the study of complex networks has expanded
across diverse scientific fields. Increasingly, science is concerned with
the structure, behavior, and evolution of complex systems ranging from
cells to ecosystems. Modern network approaches are beginning to reveal
fundamental principles of brain architecture and function, and in this
book, Olaf Sporns describes how the integrative nature of brain function
can be illuminated from a complex network perspective. Highlighting the
many emerging points of contact between neuroscience and network science,
the book serves to introduce network theory to neuroscientists and
neuroscience to those working on theoretical network models. (...)
* [47] Networks of the Brain, Olaf Sporns, 2011/11/30, The MIT Press
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