Evolution of cooperation in the snowdrift game among mobile players with random-pairing and reinforcement learning

Ning Jia and Shoufeng Ma

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 22, 5700-5710

Abstract: The evolutionary spatial game in a mobile population has attracted many researchers of biological, social and economic sciences. Considering some facts observed in the real world, this paper proposes a novel spatial evolutionary snowdrift game model with movable players. In this model, one player interacts only with the nearest neighbor in each turn, and makes decision in a reinforcement learning way. In a very large range of the parameters moving ability enhances cooperation, but under some special condition, velocity heavily depresses cooperation. Some explanations have also been given out by investigating the strategy-change behavior of players. The findings may be helpful in understanding cooperative behavior in natural and social systems consisting of mobile agents.

Keywords: Evolutionary snowdrift game; Emergence of cooperation; Moving ability; Reinforcement-learning (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:22:p:5700-5710

DOI: 10.1016/j.physa.2013.07.049

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