{"title":"Examination of graphs in Multiple Agent Genetic Networks for Iterated Prisoner's Dilemma","authors":"J. A. Brown","doi":"10.1109/CIG.2013.6633635","DOIUrl":null,"url":null,"abstract":"Multiple Agent Genetic Networks (MAGnet) are spatially structured evolutionary algorithms which move both evolving agents as well as instances of a problem about a combinatorial graph. Previous work has examined their use on the Iterated Prisoner's Dilemma, a well known non-zero sum game, in order for classification of agent types based on behaviours. Only a small complete graph was examined. In this study, a larger set of graphs with thirty-two nodes are examined. The graphs examined are: a cycle graph, two Peterson graphs with differing internal rings, a hypercube in five dimensions, and the complete graph. These graphs and properties are examined for a number of canonical agents, as well as a few interesting types which involve handshaking. It was found that the MAGnet system produces a similar classification as the smaller graph when the connectivity within the graph is high. Lower graph connectivity leads to a process by which disjoint subgraphs can be formed; this is based on the method of evolution causing a subpopulation collapse in which the number of problems on a node tends to zero and the node is removed.","PeriodicalId":158902,"journal":{"name":"2013 IEEE Conference on Computational Inteligence in Games (CIG)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Conference on Computational Inteligence in Games (CIG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIG.2013.6633635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Multiple Agent Genetic Networks (MAGnet) are spatially structured evolutionary algorithms which move both evolving agents as well as instances of a problem about a combinatorial graph. Previous work has examined their use on the Iterated Prisoner's Dilemma, a well known non-zero sum game, in order for classification of agent types based on behaviours. Only a small complete graph was examined. In this study, a larger set of graphs with thirty-two nodes are examined. The graphs examined are: a cycle graph, two Peterson graphs with differing internal rings, a hypercube in five dimensions, and the complete graph. These graphs and properties are examined for a number of canonical agents, as well as a few interesting types which involve handshaking. It was found that the MAGnet system produces a similar classification as the smaller graph when the connectivity within the graph is high. Lower graph connectivity leads to a process by which disjoint subgraphs can be formed; this is based on the method of evolution causing a subpopulation collapse in which the number of problems on a node tends to zero and the node is removed.