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Strategy evolution driven by switching probabilities in structured multi-agent systems

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  • Jianlei Zhang
  • Zengqiang Chen
  • Zhiqi Li

Abstract

Evolutionary mechanism driving the commonly seen cooperation among unrelated individuals is puzzling. Related models for evolutionary games on graphs traditionally assume that players imitate their successful neighbours with higher benefits. Notably, an implicit assumption here is that players are always able to acquire the required pay-off information. To relax this restrictive assumption, a contact-based model has been proposed, where switching probabilities between strategies drive the strategy evolution. However, the explicit and quantified relation between a player's switching probability for her strategies and the number of her neighbours remains unknown. This is especially a key point in heterogeneously structured system, where players may differ in the numbers of their neighbours. Focusing on this, here we present an augmented model by introducing an attenuation coefficient and evaluate its influence on the evolution dynamics. Results show that the individual influence on others is negatively correlated with the contact numbers specified by the network topologies. Results further provide the conditions under which the coexisting strategies can be calculated analytically.

Suggested Citation

  • Jianlei Zhang & Zengqiang Chen & Zhiqi Li, 2017. "Strategy evolution driven by switching probabilities in structured multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(13), pages 2692-2702, October.
    • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:13:p:2692-2702
    DOI: 10.1080/00207721.2017.1343406
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