Bipartite graphs as models of population structures in evolutionary multiplayer games

Details

Serval ID
serval:BIB_6BFA25F216DA
Type
Article: article from journal or magazin.
Collection
Publications
Title
Bipartite graphs as models of population structures in evolutionary multiplayer games
Journal
PLoS ONE
Author(s)
Peña  J., Rochat  Y.
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Volume
7
Number
9
Pages
e44514
Notes
10.1371/journal.pone.0044514
Abstract
<p>By combining evolutionary game theory and graph theory, âeurooegames on graphsâeuro˝ study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisonerâeuro?s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisonerâeuro?s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.</p>
Open Access
Yes
Create date
10/12/2012 16:16
Last modification date
20/08/2019 14:26
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