{"title":"多智能体形成的进化动力学","authors":"Jinjing Qin, X. Ban, Xin Li","doi":"10.1109/CCDC.2009.5192601","DOIUrl":null,"url":null,"abstract":"To probe into the internal mechanism of multi-agent formation, game theory is used to model the interaction between agents and Win-Stay-Lose-Shift strategy to instruct agents' action. Equations are introduced to formulate how agents update their positions. The Win-Stay-Lose-Shift strategy along with the update equations depicts the dynamics of multi-agent formation. And simulations are designed and performed to observe the development of multi-agent formation. The results of simulation show the feasibility of the idea in this paper.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evolutionary dynamics of multi-agent formation\",\"authors\":\"Jinjing Qin, X. Ban, Xin Li\",\"doi\":\"10.1109/CCDC.2009.5192601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To probe into the internal mechanism of multi-agent formation, game theory is used to model the interaction between agents and Win-Stay-Lose-Shift strategy to instruct agents' action. Equations are introduced to formulate how agents update their positions. The Win-Stay-Lose-Shift strategy along with the update equations depicts the dynamics of multi-agent formation. And simulations are designed and performed to observe the development of multi-agent formation. The results of simulation show the feasibility of the idea in this paper.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5192601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5192601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To probe into the internal mechanism of multi-agent formation, game theory is used to model the interaction between agents and Win-Stay-Lose-Shift strategy to instruct agents' action. Equations are introduced to formulate how agents update their positions. The Win-Stay-Lose-Shift strategy along with the update equations depicts the dynamics of multi-agent formation. And simulations are designed and performed to observe the development of multi-agent formation. The results of simulation show the feasibility of the idea in this paper.
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