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Evolution of cooperation in Axelrod tournament using cellular automata

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  • Schimit, P.H.T.
  • Santos, B.O.
  • Soares, C.A.

Abstract

Results of the Axelrod Tournament were published in 1981, and since then, evolutionary game theory emerged as an idea for understanding relations, like conflict and cooperation, between rational decision-makers. Robert Axelrod organized it as a round-robin tournament where strategies for iterated Prisoner’s Dilemma were faced in a sequence of two players game. Here, we attempt to simulate the strategies submitted to the tournament in a multi-agent context, where individuals play a two-player game with their neighbors. Each individual has one of the strategies, and it plays the Prisoner’s Dilemma with its neighbors. According to actions chosen (cooperate or defect), points of life are subtracted from their profiles. When an individual dies, some fitness functions are defined to choose the most successful strategy which the new individual will copy. Although tit-for-tat was the best strategy, on average, in the tournament, in our evolutionary multi-agent context, it has not been successful.

Suggested Citation

  • Schimit, P.H.T. & Santos, B.O. & Soares, C.A., 2015. "Evolution of cooperation in Axelrod tournament using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 204-217.
  • Handle: RePEc:eee:phsmap:v:437:y:2015:i:c:p:204-217
    DOI: 10.1016/j.physa.2015.05.111
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    1. Xueyan Li & Jing Li, 2021. "A freight transport price optimization model with multi bounded-rational customers," Transportation, Springer, vol. 48(1), pages 477-504, February.
    2. Li, Xue-yan & Li, Xue-mei & Yang, Lingrun & Li, Jing, 2018. "Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 77-92.
    3. Schimit, P.H.T., 2016. "Evolutionary aspects of spatial Prisoner’s Dilemma in a population modeled by continuous probabilistic cellular automata and genetic algorithm," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 178-188.
    4. Li, Xue-yan & Li, Xue-mei & Li, Xue-wei & Qiu, He-ting, 2017. "Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 405-419.

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