Paper Info
Title
Evolution of Cooperation on Stochastic Block Models.
Abstract
Cooperation is a major factor in the evolution of human societies. The structure of human social networks, which affects the dynamics of cooperation and other interpersonal phenomena, have common structural signatures. One of these signatures is the tendency to organize as groups. Among the generative models that network theorists use to emulate this feature is the Stochastic Block Model (SBM). In this paper, we study evolutionary game dynamics on SBM networks. Using a recently-discovered duality between evolutionary games and coalescing random walks, we obtain analytical conditions such that natural selection favors cooperation over defection. We calculate the transition point for each community to favor cooperation. We find that a critical inter-community link creation probability exists for given group density, such that the overall network supports cooperation even if individual communities inhibit it. As a byproduct, we present mean-field solutions for the critical benefit-to-cost ratio which perform with remarkable accuracy for diverse generative network models, including those with community structure and heavy-tailed degree distributions. We also demonstrate the generalizability of the results to arbitrary two-player games.
Year
Venue
Field
2018
arXiv: Social and Information Networks
Community structure,Social network,Computer science,Random walk,Natural selection,Theoretical computer science,Stochastic block model,Duality (optimization),Artificial intelligence,Generative grammar,Machine learning,Network model
DocType
Volume
Citations 
Journal
abs/1807.03093
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Babak Fotouhi112.75
Naghmeh Momeni243.87
Benjamin Allen372.51
Martin Nowak49424.39