{"title":"基于群体智能的进化博弈解决方案","authors":"Zhijie Li, Xiang-dong Liu, X. Duan, Cun-rui Wang","doi":"10.1109/PACCS.2010.5626955","DOIUrl":null,"url":null,"abstract":"To address the problem of quick searching for evolutionary stable strategy in replicated dynamic mechanism, a solving algorithm based on parallel particle sub-swarm optimization (PSSO) is proposed. Firstly, evaluating function is introduced to integrate multiple objectives of all strategies. Secondly, multiplier method is used to derivate the fitness function. Finally, the optimal solution of strategy selection scheme is generated. The results show that the proposed algorithm performs better than standard particle swarm optimization in terms of optimal solution.","PeriodicalId":431294,"journal":{"name":"2010 Second Pacific-Asia Conference on Circuits, Communications and System","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A swarm-intelligence based solution for evolutionary game\",\"authors\":\"Zhijie Li, Xiang-dong Liu, X. Duan, Cun-rui Wang\",\"doi\":\"10.1109/PACCS.2010.5626955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To address the problem of quick searching for evolutionary stable strategy in replicated dynamic mechanism, a solving algorithm based on parallel particle sub-swarm optimization (PSSO) is proposed. Firstly, evaluating function is introduced to integrate multiple objectives of all strategies. Secondly, multiplier method is used to derivate the fitness function. Finally, the optimal solution of strategy selection scheme is generated. The results show that the proposed algorithm performs better than standard particle swarm optimization in terms of optimal solution.\",\"PeriodicalId\":431294,\"journal\":{\"name\":\"2010 Second Pacific-Asia Conference on Circuits, Communications and System\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second Pacific-Asia Conference on Circuits, Communications and System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACCS.2010.5626955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second Pacific-Asia Conference on Circuits, Communications and System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACCS.2010.5626955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A swarm-intelligence based solution for evolutionary game
To address the problem of quick searching for evolutionary stable strategy in replicated dynamic mechanism, a solving algorithm based on parallel particle sub-swarm optimization (PSSO) is proposed. Firstly, evaluating function is introduced to integrate multiple objectives of all strategies. Secondly, multiplier method is used to derivate the fitness function. Finally, the optimal solution of strategy selection scheme is generated. The results show that the proposed algorithm performs better than standard particle swarm optimization in terms of optimal solution.