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  March 2008

SOCNET March 2008

Subject:

complexity digest gleanings for this week

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Sat, 1 Mar 2008 21:25:52 -0500

Content-Type:

TEXT/PLAIN

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (152 lines)

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

 Barry Wellman
 _______________________________________________________________________

  S.D. Clark Professor of Sociology, FRSC              NetLab Director
  Centre for Urban & Community Studies           University of Toronto
  455 Spadina Avenue          Room 418          Toronto Canada M5S 2G8
  http://www.chass.utoronto.ca/~wellman            fax:+1-416-978-7162
  Updating history:     http://chass.utoronto.ca/oldnew/cybertimes.php
         Elvis wouldn't be singing "Return to Sender" these days
 _______________________________________________________________________

Predicting Human Interactive Learning by Regret-Driven Neural Networks ,
Science

Excerpts: An unexpectedly simple neural network model that includes
feedback driven by regret predicts human behavior in strategic games and
outperforms existing models of learning. (...) We found that even very
simple learning networks, driven by regret-based feedback, accurately
predict observed human behavior in different experiments on 21 games with
unique equilibria in mixed strategies. Introducing regret in the feedback
dramatically improved the performance of the neural network. We show that
regret-based models provide better predictions of learning than
established economic models.

* [6] Predicting Human Interactive Learning by Regret-Driven Neural
Networks,
Davide Marchiori ,  Massimo Warglien, 08/02/22, Science : 1111-1113.

[6] http://www.sciencemag.org/cgi/content/full/319/5866/1111

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

SCImago Journal Rankings , SCImago Journal & Country Rank

Excerpts: The Science Citation Index and associated Journal Citation
Report (JCR) has long dominated the measurement of scholarly citation, but
SCImago Journal and Country Rank, is a new alternative database of journal
citation metrics developed by researchers in Spain. Unlike the JCR (which
is available to subscribers only), SCImago is freely available online, and
SCImago offers important improvements, compared to the JCR such as
weighting citations from journals according to how highly cited the
journal itself is. For further information please read the announcement on
the BioMed Central blog.

* [13] SCImago Journal Rankings, SCImago Journal & Country Rank

[13]
http://news.biomedcentral.com/t/2020138/10128546/871228/0/?u=aHR0cDovL3d3dy5zY2ltYWd
vanIuY29tLw%3d%3d&x=508f7a58

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


Excerpts: A crop of websites is making networking among scientists easier
than ever. (...) The success of social-networking websites such as
MySpace, Facebook and LinkedIn shows the power of the Internet not only to
cultivate, but to capitalize on, friendships. Although online networks may
seem impersonal, they can do something for scientists that a handshake
cannot: highlight common research interests without leaving the comfort of
your desk. Say goodbye to name tags and awkward introductions - say hello
to profiles and blogs. In the search for jobs, mentors, collaborators or
data, these cyber-social mixers are revealing new ways to gain career
advice, create collaborations and share resources.

* [14] The New Networking Nexus, Virginia Gewin, 08/02/21, DOI:
10.1038/nj7181-1024a, Nature 451

[14] http://www.nature.com/naturejobs/2008/080221/full/nj7181-1024a.html



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

 A Mathematical Formalism for Agent-based Modeling , arXiv

Excerpt: Many complex systems can be modeled as multiagent systems in
which the constituent entities (agents) interact with each other. The
global dynamics of such a system is determined by the nature of the local
interactions among the agents. Since it is difficult to formally analyze
complex multiagent systems, they are often studied through computer
simulations. While computer simulations can be very useful, results
obtained through simulations do not formally validate the observed
behavior. (...) The paper contains a sampling of the mathematical results
from the literature to show how finite dynamical systems can be used to
carry out a rigorous study of the properties of multiagent systems (...).

* [22] A Mathematical Formalism for Agent-based Modeling, Reinhard
Laubenbacher, Abdul S. Jarrah, Henning Mortveit, and S.S. Ravi,
2007/12/31,
DOI: 0801.0249, arXiv
* Contributed by [23] Carlos Gershenson

[22] http://uk.arXiv.org/abs/0801.0249

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

 Set-based Complexity and Biological Information , arXiv

Abstract: It is not obvious what fraction of all the potential information
residing in the molecules and structures of living systems is significant
or meaningful to the system. Sets of random sequences or identically
repeated sequences, for example, would be expected to contribute little or
no useful information to a cell. This issue of quantitation of information
is important since the ebb and flow of biologically significant
information is essential to our quantitative understanding of biological
function and evolution.  Motivated specifically by these problems of
biological information, we propose here a class of measures to quantify
the contextual nature of the information in sets of objects, based on
Kolmogorov's intrinsic complexity. Such measures discount both random and
redundant information and are inherent in that they do not require a
defined state space to quantify the information. The maximization of this
new measure, which can be formulated in terms of the universal information
distance, appears to have several useful and interesting properties, some
of which we illustrate with examples.

* [24] Set-based Complexity and Biological Information, David J. Galas,
Matti
Nykter, Gregory W. Carter, Nathan D. Price, Ilya Shmulevich, 2008/01/25,
DOI:
0801.4024, arXiv
* Contributed by [25] Carlos Gershenson

[24] http://uk.arXiv.org/abs/0801.4024

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

 STOP Terrorism Software: Technology For Analysis And Forecasting Of
Terrorism , Science Daily

Excerpts: Researchers at the University of Maryland's Institute for
Advanced Computer Studies (UMIACS) have developed the SOMA Terror
Organization Portal (STOP) allowing analysts to query automatically
learned rules on terrorist organization behavior, forecast potential
behavior based on these rules, and, most importantly, to network with
other analysts examining the same subjects. SOMA (Stochastic Opponent
Modeling Agents) is a formal, logical-statistical reasoning framework that
uses data about past behavior of terror groups in order to learn rules
about the probability of an organization, community, or person taking
certain actions in different situations.

* [54] STOP Terrorism Software: Technology For Analysis And Forecasting Of
Terrorism, 08/02/27, ScienceDaily

[54] http://www.sciencedaily.com/releases/2008/02/080226092812.htm

_____________________________________________________________________
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

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