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Evolution of Cooperative Behavior in a Spatial Iterated Prisoner's Dilemma Game with Different Representation Schemes of Game Strategies

机译:不同代表战略不同代表计划的空间迭代囚犯困境游戏中合作行为的演变

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The iterated prisoner's dilemma (IPD) game has been frequently used to examine the evolution of cooperative behavior among agents in the field of evolutionary computation. A number of factors are known to be related to the evolution of cooperative behavior. One well-known factor is spatial relations among agents. The IPD game is often played in a grid-world. Such a spatial IPD game has a neighborhood structure which is used for local opponent selection in the IPD game and local parent selection in genetic operations. Another important factor is the choice of a representation scheme to encode each strategy. Different representation schemes often lead to totally different results. Whereas the choice of a representation scheme is known to be important, a mixture of different representation schemes has not been examined for the spatial IPD game in the literature. This means that a population of homogeneous agents with the same representation scheme has been assumed. In this paper, we introduce a different situation to the spatial IPD game in order to examine the evolution of cooperative behavior under more general assumptions. The main novelty of our spatial IPD game is the use of a mixture of different representation schemes. This means that we use a population of inhomogeneous agents with different representation schemes. Another novelty is the use of two neighborhood structures, each of which is used for local opponent selection and local parent selection. Under these specifications, we show a number of interesting observations on the evolution of cooperative behavior.
机译:迭代囚犯的困境(IPD)游戏经常用于检查进化计算领域的代理商之间的合作行为的演变。已知许多因素与合作行为的演变有关。一个众所周知的因素是代理商之间的空间关系。 IPD游戏经常在网格世界中播放。这种空间IPD游戏具有邻域结构,用于在IPD游戏中的本地对手选择和遗传操作中的本地父母选择。另一个重要因素是选择编码每个策略的表示方案。不同的表示方案通常会导致完全不同的结果。然而,已知一种表示方案的选择是重要的,但是在文献中的空间IPD游戏尚未检查不同代表方案的混合。这意味着假设具有相同表示方案的均匀试剂的群体。在本文中,我们向空间IPD游戏介绍了一个不同的情况,以便在更一般的假设下检查合作行为的演变。我们的空间IPD游戏的主要新颖性是使用不同代表方案的混合。这意味着我们使用具有不同代表​​方案的非均匀代理。另一个新颖性是使用两个邻域结构,每个结构用于本地对手选择和本地父级选择。在这些规范下,我们对合作行为的演变显示了许多有趣的观察。

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