{"title":"基于粒子群算法的n选择IPD博弈的协同进化学习","authors":"Xiaoyang Wang, Huiyou Chang, Yang Yi, Yibin Lin","doi":"10.1109/NaBIC.2012.6402245","DOIUrl":null,"url":null,"abstract":"A particle swarm optimization (PSO) approach towards the development of strategy co-evolution for multiple choices IPD game is presented. It is demonstrated that, birds can play IPD with multiple choices, and the co-evolutionary behaviors are influenced by social environment.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Co-evolutionary learning in the N-choice IPD game with PSO algorithm\",\"authors\":\"Xiaoyang Wang, Huiyou Chang, Yang Yi, Yibin Lin\",\"doi\":\"10.1109/NaBIC.2012.6402245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A particle swarm optimization (PSO) approach towards the development of strategy co-evolution for multiple choices IPD game is presented. It is demonstrated that, birds can play IPD with multiple choices, and the co-evolutionary behaviors are influenced by social environment.\",\"PeriodicalId\":103091,\"journal\":{\"name\":\"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NaBIC.2012.6402245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NaBIC.2012.6402245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Co-evolutionary learning in the N-choice IPD game with PSO algorithm
A particle swarm optimization (PSO) approach towards the development of strategy co-evolution for multiple choices IPD game is presented. It is demonstrated that, birds can play IPD with multiple choices, and the co-evolutionary behaviors are influenced by social environment.