{"title":"一个可以从经验中学习的游戏机器人","authors":"Raafat Ahmed Abd El-Azim, A. Ueno, S. Tatsumi","doi":"10.1109/HSI.2008.4581479","DOIUrl":null,"url":null,"abstract":"We present a new approach for online learning an x-o game strategy by humanoid robot ldquohoap-3rdquo*. No preset data for game playing are provided in advance. The proposed system mechanism simulates human decision making to carry out the online game learning. ldquohaop-3rdquo autonomously gains experience needed for learning the game strategy from the human partner. The more intelligent human partner, the faster humanoid robot ldquohoap-3rdquo learning.","PeriodicalId":139846,"journal":{"name":"2008 Conference on Human System Interactions","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A game playing robot that can learn from experience\",\"authors\":\"Raafat Ahmed Abd El-Azim, A. Ueno, S. Tatsumi\",\"doi\":\"10.1109/HSI.2008.4581479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a new approach for online learning an x-o game strategy by humanoid robot ldquohoap-3rdquo*. No preset data for game playing are provided in advance. The proposed system mechanism simulates human decision making to carry out the online game learning. ldquohaop-3rdquo autonomously gains experience needed for learning the game strategy from the human partner. The more intelligent human partner, the faster humanoid robot ldquohoap-3rdquo learning.\",\"PeriodicalId\":139846,\"journal\":{\"name\":\"2008 Conference on Human System Interactions\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Conference on Human System Interactions\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HSI.2008.4581479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Conference on Human System Interactions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HSI.2008.4581479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A game playing robot that can learn from experience
We present a new approach for online learning an x-o game strategy by humanoid robot ldquohoap-3rdquo*. No preset data for game playing are provided in advance. The proposed system mechanism simulates human decision making to carry out the online game learning. ldquohaop-3rdquo autonomously gains experience needed for learning the game strategy from the human partner. The more intelligent human partner, the faster humanoid robot ldquohoap-3rdquo learning.
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