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The paper deals with the repeated prisoner’s dilemma and evolving strategies for this game. For evolving strategies, an algorithm has been developed that simulates the evolution of strategies in an iterated prisoner’s dilemma, using selection, mutation and crossover operators. A new crossover operator has been developed to maximize the total population gain in the repeated prisoner’s dilemma.

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Genetic Algorithm for Repeated Prisoner’s Dilemma

  • 会议论文

  • 发表日期：

    2025年

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  • Nikita A. Gruzdev

摘要

The paper deals with the repeated prisoner’s dilemma and evolving strategies for this game. For evolving strategies, an algorithm has been developed that simulates the evolution of strategies in an iterated prisoner’s dilemma, using selection, mutation and crossover operators. A new crossover operator has been developed to maximize the total population gain in the repeated prisoner’s dilemma.