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On evolving fixed pattern strategies for Iterated Prisoner's Dilemma

机译:关于迭代囚徒困境的发展的固定模式策略

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This paper describes the social evolution of an environment where all individuals are repeating patterns of behaviour. The paper follows Axelrod's work [1] of computer simulations of Iterated Prisoner's Dilemma (IPD), which is widely regarded as a standard model for the evolution of cooperation. Previous studies by Axelrod [2], Hirshleifer and Coll [3], Lindgren [4], Fogel [5], Darwen and Yao [6] focused on strategies that are history dependent. In other words, these strategies use the outcome of the opponent's past game history in making a decision on a given move. This includes the most well-known strategy, tit-for-tat.The way strategies are encoded in the computer program reflects the model's assumption concerning individual decision-making. In this paper, we study environments where all players are simply repeating patterns of behaviour without using past game history. In doing so, a genetic algorithm is used to evolve such strategies in a co-evolution environment. Simulations indicate that such an environment is harmful to the evolution of cooperation.
机译:本文描述了一个环境的社会演变,其中所有个人都在重复行为模式。本文遵循Axelrod对迭代囚徒困境(IPD)进行计算机仿真的工作[1],该工作被广泛视为合作发展的标准模型。 Axelrod [2],Hirshleifer和Coll [3],Lindgren [4],Fogel [5],Darwen和Yao [6]先前的研究集中在依赖于历史的策略上。换句话说,这些策略使用对手过去的游戏历史的结果来决定给定的举动。这包括最著名的策略,“针锋相对”。计算机程序中策略的编码方式反映了模型关于个人决策的假设。在本文中,我们研究了所有玩家都在不使用过去游戏历史的情况下简单地重复行为模式的环境。在此过程中,遗传算法用于在协同进化环境中发展此类策略。模拟表明,这种环境不利于合作的发展。

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