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lots today.
To quote my late mentor, James Durante, "Everybody's getting into the
act." Sometimes originally; sometimes reinventing ...
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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Evolution of cooperation on dynamical graphs , Biosystems
Excerpt: (...) Earlier works have shown that population structure is one
of the mechanisms promoting cooperation. However, most studies had assumed
that the interaction network can be described by a regular graph
(homogeneous degree distribution). (...) Here we investigate the fixation
probability of the cooperator strategy in the prisoner's dilemma, when
interaction network is a random regular graph, a random graph or a
scale-free graph and the interaction network is allowed to change.We show
that the fixation probability of the cooperator strategy is lower when the
interaction topology is described by a dynamical graph compared to a
static graph. Even a limited network dynamics significantly decreases the
fixation probability of cooperation,
* [15] Evolution of cooperation on dynamical graphs, Ã^Ádám Kun , István
Scheuring, 2009-06-01, DOI: 10.1016/j.biosystems.2008.11.009 [15]
http://dx.doi.org/10.1016/j.biosystems.2008.11.009
----------------------------------
The evolution of cooperation on structured population , Physica A
Excerpt: (...) the theoretical analysis for the enhancement of cooperation
on a heterogenous network is still short. In this work, we first model a
heterogenous network by three simple networks with increasing complexity
on their network structures. Then according to a master equation we
develop the replication equations for the evolution of cooperation on
these networks. The explicit formulations for the cooperator frequency on
these networks are deduced and the relationship between the cooperator
frequency and the network heterogeneity is discussed.
* [17] The evolution of cooperation on structured population, Xiaolan Qian
, Junzhong Yang, 1 August 2009, DOI: 10.1016/j.physa.2009.04.025, Physica
A: Statistical Mechanics and its Applications, Volume 388, Issues 15-16,
Pages 3143-3154 [17] http://dx.doi.org/10.1016/j.physa.2009.04.025
---------------------------
Evolving learning rules and emergence of cooperation in spatial
prisoner's dilemma , Journal of Theoretical Biology
Excerpt: In the evolutionary Prisoner's dilemma (PD) game, agents play
with each other and update their strategies in every generation according
to some microscopic dynamical rule. In its spatial version, agents do not
play with every other but, instead, interact only with their neighbours,
thus mimicking the existing of a social or contact network that defines
who interacts with whom. (...) We show that in a well-mixed population the
evolutionary outcome is always full defection. (...) the results are also
very different if update rules are fixed or evolve with the strategies.
(...) We describe the new and rich variety of final outcomes that arise
from this co-evolutionary dynamics.
* [19] Evolving learning rules and emergence of cooperation in spatial
prisoner's dilemma, Luis G. Moyano , Angel Sánchez, 7 July 2009, DOI:
10.1016/j.jtbi.2009.03.002, Journal of Theoretical Biology Volume 259,
Issue 1,* Contributed by [20] Segismundo
[19] http://dx.doi.org/10.1016/j.jtbi.2009.03.002
--------------------------
Getting in Touch with Your Friends , Science
Summary: Microbes use a broad palette of chemical transformations to
harvest energy and nutrients, but they do not always accomplish these
conversions on their own. Particularly in anaerobic environments, various
metabolisms are stimulated by, or depend upon, partnerships (1). In this
form of interactionâ^À^Ôtermed syntrophyâ^À^Ôone organism typically
converts the primary resource to an intermediate that can be used by a
partner (which perhaps passes it along to the next, and so on). In other
cases, one partner may use a resource and provide a different type of
service in return, such as a trace vitamin or motility. Recent studies are
beginning to shed light on the mechanisms by which such partners
communicate and interact and on how such interactions emerge in the first
place.
* [22] Getting in Touch with Your Friends, Christopher J. Marx,
2009/05/29, DOI: 10.1126/science.1173088, Science Vol. 324. no. 5931, pp.
1150 - 1151 [22] http://dx.doi.org/10.1126/science.1173088
-----------------------
Summary: (...) hypergraphs generalize graphs by allowing for multilateral
relationships between the nodes, which often results in a more precise
description of biological processes. Hypergraphs thus provide an important
approach for representing biological networks, whose potential has not
been fully exploited yet. We therefore expect that applications of
hypergraph theory in computational biology will increase in the near
future.
* [23] Hypergraphs and Cellular Networks, Klamt S, Haus U-U, Theis F,
2009/05/29, DOI: 10.1371/journal.pcbi.1000385, PLoS Comput Biol 5(5):
e1000385 [23] http://dx.doi.org/10.1371/journal.pcbi.1000385
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The Computation of Social Behavior , Science
Excerpt: Neuroscientists are beginning to advance explanations of social
behavior in terms of underlying brain mechanisms. Two distinct networks of
brain regions have come to the fore. The first involves brain regions that
are concerned with learning about reward and reinforcement. These same
reward-related brain areas also mediate preferences that are social in
nature even when no direct reward is expected. The second network focuses
on regions active when a person must make estimates of another
personâ^À^Ùs intentions.
* [25] The Computation of Social Behavior, Timothy E. J. Behrens, Laurence
T. Hunt, Matthew F. S. Rushworth, 2009/05/29, DOI: 10.1126/science.
1169694, Science Vol. 324. no. 5931, pp. 1160 - 1164
[25] http://dx.doi.org/10.1126/science.1169694
----------------------------
Abstract: We study how networks with a fixed number of nodes but variable
density of edges evolve under very general conditions of nonlinear
attachment and detachment. Considering the probabilities each node has of
gaining or losing edges to have two components -- a local dependence on
degree and a global one on density -- the degree distribution relaxes
towards stationary states which can be either quite homogeneous or highly
heterogeneous, with scale-free solutions at a critical point. As an
illustration, we show how choices of functions based on biological
considerations give rise to network evolution which is in good agreement
with data on brain development. In particular, the phenomenon known as
synaptic pruning and the emergence of highly heterogeneous, small--world
topologies are features well described, while the critical point exhibits
a peak in unsynchronizability.
Evolving networks and their application to synaptic pruning, Samuel
Johnson, J. Marro, and Joaquin J. Torres, 2009/05/24, arXiv:0905.3759
[29] http://arXiv.org/abs/0905.3759
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Excerpt: We use techniques from network science to study correlations in
the foreign exchange (FX) market over the period 1991--2008. We consider
an FX market network in which each node represents an exchange rate and
each weighted edge represents a time-dependent correlation between the
rates. To provide insights into the clustering of the exchange rate time
series, we investigate dynamic communities in the network. We show that
there is a relationship between an exchange rate's functional role within
the market and its position within its community and use a node-centric
community analysis to track the time dynamics of this role.
* [30] Dynamical Clustering of Exchange Rates, Daniel J. Fenn, Mason A.
Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson,
Nick S. Jones, 2009/05/29, arXiv:0905.4912 http://arXiv.org/abs/0905.4912
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17. The survival of the weakest in networks , Journal Computational &
Mathematical Organization Theory
We study here dynamic antagonism in a fixed network, represented as a
graph G of n vertices. In particular, we consider the case of k=n
particles walking randomly independently around the network. Each particle
belongs to exactly one of two antagonistic species, none of which can give
birth to children. When two particles meet, they are engaged in a
(sometimes mortal) local fight. The outcome of the fight depends on the
species to which the particles belong. Our problem is to predict the
eventual chances of species survival. We prove that this can indeed be
done in expected polynomial time.
The survival of the weakest in networks, S. Nikoletseas, C. Raptopoulos,
P. Spirakis, 2009/06/01, DOI: 10.1007/s10588-008-9050-2, Journal
Computational & Mathematical Organization Theory, vol. 15, issue 2 [31]
http://dx.doi.org/10.1007/s10588-008-9050-2
----------------------------
The norm game: punishing enemies and not friends , Journal of Economic
Interaction and Coordination
Three mean field models of the norm game are explored analytically. The
strategies are: to obey the norm or not and to punish those who break it
or not. The punishment, the temptation, the anger and the punishment cost
are modeled by four parameters; for the fixed points, only two ratios of
these parameters are relevant. For each model, we consider its variant
with two mutually punishing groups. We show that all solutions are the
same as for the case in one group. This means in particular, that in both
groups the amount of defectors is the same.
* [33] The norm game: punishing enemies and not friends, K. Kulakowski,
2009/06/01, DOI: 10.1007/s11403-009-0045-y, Journal of Economic
Interaction and Coordination, Volume 4, Issue 1
http://dx.doi.org/10.1007/s11403-009-0045-y [34]
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18. Symmetry in world trade network , Journal of Systems Science and
Complexity
Symmetry of the world trade network provides a novel perspective to
understand the world-wide trading system. However, symmetry in the world
trade network (WTN) has been rarely studied so far. In this paper, the
authors systematically explore the symmetry in WTN. The authors explore
the size and structure of its automorphism group, through which the
authors find that WTN is symmetric, particularly, locally symmetric to a
certain degree. Furthermore, the authors investigate the structure and
function of the symmetric motifs, coming to the conclusion that local
symmetry will have great effect on the stability of the WTN.
* [35] Symmetry in world trade network, Hui Wang, Guangle Yan, Yanghua
Xiao, 2009/06/01, DOI: 10.1007/s11424-009-9163-9, Journal of Systems
Science and Complexity , Volume 22, Issue 2
[35] http://dx.doi.org/10.1007/s11424-009-9163-9
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18.02. Business fluctuations and bankruptcy avalanches in an evolving
network economy , Journal of Economic Interaction and Coordination
We analyze the properties of a three-sector network economy characterized
by credit relationships connecting downstream and upstream firms and
credit relationships connecting firms and banks. The network topology
changes over time and the output of simulations shows that a business
cycle at the macroeconomic level can develop as a consequence of the
complex interaction of the heterogeneous financial conditions of the
agents involved. The bankruptcy of one agent can bring about the
bankruptcy of one or more other agents in a snowball effect, depending on
the network structure and the incidence of non- performing loans on
balance sheets of agents involved.
* [39] Business fluctuations and bankruptcy avalanches in an evolving
network economy, Domenico Delli Gatti et al, 2009/06/01, DOI: 10.1007/
s11403-009-0054-x, Journal of Economic Interaction and Coordination,
1860-711X 1860-7128 (Online)
[39] http://dx.doi.org/10.1007/s11403-009-0054-x
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Dynamical Processes on Complex Networks (Book) , Cambridge University
Press
Cover The availability of large data sets have allowed researchers
to uncover complex properties such as large-scale fluctuations and
heterogeneities in many networks which have lead to the breakdown of
standard theoretical frameworks and models. Until recently these systems
were considered as haphazard sets of points and connections. Recent
advances have generated a vigorous research effort in understanding the
effect of complex connectivity patterns on dynamical phenomena. E.g. a
vast number of everyday systems, from the brain to ecosystems and the
Internet, can be represented as large complex networks. This new, recent
account presents a comprehensive explanation of these effects.
* [41] Dynamical Processes on Complex Networks, Alain Barrat, Marc
Barthelemy, Alessandro Vespignani, 2008/11/28, Cambridge University Press
http://www.amazon.com/Dynamical-Processes-Complex-Networks-Barrat/dp/0521879507
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