We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents' learning behavior. We study this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. We argue that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable.
%0 Journal Article
%1 Skyrms:2000p404
%A Skyrms, B
%A Pemantle, R
%D 2000
%J P Natl Acad Sci USA
%K Dynamical Games Graphs,
%N 16
%P 9340--9346
%T A dynamic model of social network formation
%V 97
%X We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents' learning behavior. We study this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. We argue that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable.
@article{Skyrms:2000p404,
abstract = {We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents' learning behavior. We study this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. We argue that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable.},
added-at = {2009-02-08T16:38:56.000+0100},
affiliation = {Univ Calif Irvine, Sch Social Sci, Irvine, CA 92607 USA},
author = {Skyrms, B and Pemantle, R},
biburl = {https://www.bibsonomy.org/bibtex/20c4b652aa477666b64c29b93ffb48869/svsegbro},
date-added = {2008-05-29 17:28:53 +0200},
date-modified = {2008-08-08 17:00:55 +0200},
interhash = {f70fda00567e1fe26c1dc6602a46e119},
intrahash = {0c4b652aa477666b64c29b93ffb48869},
journal = {P Natl Acad Sci USA},
keywords = {Dynamical Games Graphs,},
language = {English},
local-url = {file://localhost/Users/sven/Documents/Papers/2000/Skyrms/P%20Natl%20Acad%20Sci%20USA%202000%20Skyrms.pdf},
month = Jan,
number = 16,
pages = {9340--9346},
rating = {0},
read = {Yes},
timestamp = {2009-02-08T16:39:00.000+0100},
title = {A dynamic model of social network formation},
uri = {papers://B7B184F3-8CE5-4C43-B61C-B7952DE67982/Paper/p404},
volume = 97,
year = 2000
}