LISTSERV mailing list manager LISTSERV 16.0

Help for SOCNET Archives


SOCNET Archives

SOCNET Archives


SOCNET@LISTS.UFL.EDU


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

SOCNET Home

SOCNET Home

SOCNET  June 2009

SOCNET June 2009

Subject:

complexity digest gleanings

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Fri, 5 Jun 2009 21:05:09 -0400

Content-Type:

TEXT/PLAIN

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (280 lines)

*****  To join INSNA, visit http://www.insna.org  *****

lots today.

To quote my late mentor, James Durante, "Everybody's getting into the
act." Sometimes originally; sometimes reinventing ...

 Barry Wellman
 _______________________________________________________________________

  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
 _______________________________________________________________________

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, ├^┴d├ím Kun , Istv├ín
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 interactionÔ^└^ďtermed syntrophyÔ^└^ďone 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

--------------------------------------

 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
personÔ^└^┘s 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

-------------------------------------


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

_________________________________________________________________

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]

_________________________________________________________________

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

------------------

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

---------------------

 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

------------

_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.

Top of Message | Previous Page | Permalink

Advanced Options


Options

Log In

Log In

Get Password

Get Password


Search Archives

Search Archives


Subscribe or Unsubscribe

Subscribe or Unsubscribe


Archives

November 2021
October 2021
September 2021
August 2021
July 2021
June 2021
May 2021
April 2021
March 2021
February 2021
January 2021
December 2020
November 2020
October 2020
September 2020
August 2020
July 2020
June 2020
May 2020
April 2020
March 2020
February 2020
January 2020
December 2019
November 2019
October 2019
September 2019
August 2019
July 2019
June 2019
May 2019
April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008, Week 62
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
December 2006
November 2006
October 2006
September 2006
August 2006
July 2006
June 2006
May 2006
April 2006
March 2006
February 2006
January 2006
December 2005
November 2005
October 2005
September 2005
August 2005
July 2005
June 2005
May 2005
April 2005
March 2005
February 2005
January 2005
December 2004
November 2004
October 2004
September 2004
August 2004
July 2004
June 2004
May 2004
April 2004
March 2004
February 2004
January 2004
December 2003
November 2003
October 2003
September 2003
August 2003
July 2003
June 2003
May 2003
April 2003
March 2003
February 2003
January 2003
December 2002
November 2002
October 2002
September 2002
August 2002
July 2002
June 2002
May 2002
April 2002
March 2002
February 2002
January 2002
December 2001
November 2001
October 2001
September 2001
August 2001
July 2001
June 2001
May 2001

ATOM RSS1 RSS2



LISTS.UFL.EDU

CataList Email List Search Powered by the LISTSERV Email List Manager