Sustaining cooperation on networks: an analytical study based on evolutionary game theory

Raghunandan, MA and Subramanian, CA (2012) Sustaining cooperation on networks: an analytical study based on evolutionary game theory. In: 11th International Conference on Autonomous Agents and Multiagent Systems, 2012, Richland, SC.

PDF Auto_Agen_Mul_Sys_2_913_2012.pdf - Published Version Restricted to Registered users only Download (706kB) | Request a copy

Abstract

We analytically study the role played by the network topology in sustaining cooperation in a society of myopic agents in an evolutionary setting. In our model, each agent plays the Prisoner's Dilemma (PD) game with its neighbors, as specified by a network. Cooperation is the incumbent strategy, whereas defectors are the mutants. Starting with a population of cooperators, some agents are switched to defection. The agents then play the PD game with their neighbors and compute their fitness. After this, an evolutionary rule, or imitation dynamic is used to update the agent strategy. A defector switches back to cooperation if it has a cooperator neighbor with higher fitness. The network is said to sustain cooperation if almost all defectors switch to cooperation. Earlier work on the sustenance of cooperation has largely consisted of simulation studies, and we seek to complement this body of work by providing analytical insight for the same. We find that in order to sustain cooperation, a network should satisfy some properties such as small average diameter, densification, and irregularity. Real-world networks have been empirically shown to exhibit these properties, and are thus candidates for the sustenance of cooperation. We also analyze some specific graphs to determine whether or not they sustain cooperation. In particular, we find that scale-free graphs belonging to a certain family sustain cooperation, whereas Erdos-Renyi random graphs do not. To the best of our knowledge, ours is the first analytical attempt to determine which networks sustain cooperation in a population of myopic agents in an evolutionary setting.

Item Type:	Conference Paper
Publisher:	Association for Computing Machinery
Additional Information:	Copyright of this article belongs to Association for Computing Machinery.
Keywords:	Agent Interaction; Evolution of Cooperation; Emergent behavior
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	29 Nov 2013 05:39
Last Modified:	29 Nov 2013 05:39
URI:	http://eprints.iisc.ac.in/id/eprint/47829

Actions (login required)

View Item