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Properties of Prisoner's Dilemma Game based on genetic algorithm

机译:基于遗传算法的囚徒困境博弈的性质

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Evolutionary games are widely studied in the fields of biology, sociology, economics and informatics. People's interests focus on how cooperation emerged in a system that individuals are selfish. We studied the iterated Prisoner's Dilemma Game evolved on BA network with genetic algorithm. Nodes in network could remember the game historical strategies and coded into gene. We show that memory length has gentle effect on cooperation level, and that some characteristic genes and frequently used genes emerge after some generations. We also find that cooperate strategy distributed on different degree-nodes equably. These findings give new perspectives to the illustration of cooperation behavior in biological group and society.
机译:进化博弈在生物学,社会学,经济学和信息学领域得到了广泛的研究。人们的利益集中于在个人自私的系统中合作是如何出现的。我们用遗传算法研究了在BA网络上演化的迭代囚徒困境博弈。网络中的节点可以记住游戏的历史策略并将其编码为基因。我们表明记忆长度对合作水平有温和的影响,并且一些特征基因和经常使用的基因经过几代人出现。我们还发现合作策略在不同度数节点上均等分布。这些发现为生物学团体和社会中合作行为的阐释提供了新的视角。

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