{"title":"机器人为赢而战:进化足球策略","authors":"A. Agah, K. Tanie","doi":"10.1109/ROBOT.1997.620107","DOIUrl":null,"url":null,"abstract":"Automatic development and learning of robot soccer strategies are presented in this paper. It is shown that using a novel control system, it is possible to allow teams of robots to acquire strategies for playing a better game of soccer through successive generations, utilizing simulated evolution. A number of soccer techniques, as developed through robot games, are discussed. The mechanism presented in the paper is suitable for other tasks requiring multiple robots to interact and cooperate in teams.","PeriodicalId":225473,"journal":{"name":"Proceedings of International Conference on Robotics and Automation","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Robots playing to win: evolutionary soccer strategies\",\"authors\":\"A. Agah, K. Tanie\",\"doi\":\"10.1109/ROBOT.1997.620107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic development and learning of robot soccer strategies are presented in this paper. It is shown that using a novel control system, it is possible to allow teams of robots to acquire strategies for playing a better game of soccer through successive generations, utilizing simulated evolution. A number of soccer techniques, as developed through robot games, are discussed. The mechanism presented in the paper is suitable for other tasks requiring multiple robots to interact and cooperate in teams.\",\"PeriodicalId\":225473,\"journal\":{\"name\":\"Proceedings of International Conference on Robotics and Automation\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of International Conference on Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROBOT.1997.620107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOT.1997.620107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robots playing to win: evolutionary soccer strategies
Automatic development and learning of robot soccer strategies are presented in this paper. It is shown that using a novel control system, it is possible to allow teams of robots to acquire strategies for playing a better game of soccer through successive generations, utilizing simulated evolution. A number of soccer techniques, as developed through robot games, are discussed. The mechanism presented in the paper is suitable for other tasks requiring multiple robots to interact and cooperate in teams.
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