{"title":"对多人游戏中非玩家学习代理的有效教学支持","authors":"Sotaro Tsutsui, Naoki Fukuta","doi":"10.1109/AGENTS.2018.8459966","DOIUrl":null,"url":null,"abstract":"Giving human knowledge to learning agents is a good way to speed up the process of reinforcement learning for learning agents. To give human knowledge to learning agent efficiently, it is important to estimate whether or not agents need more knowledge. In this paper, we present our approach to realize efficient teaching on an application which can show the users the progress of learning in a video game.","PeriodicalId":248901,"journal":{"name":"2018 IEEE International Conference on Agents (ICA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Efficient Teaching Support to Non-player Learning Agents on Multiplayer Games\",\"authors\":\"Sotaro Tsutsui, Naoki Fukuta\",\"doi\":\"10.1109/AGENTS.2018.8459966\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Giving human knowledge to learning agents is a good way to speed up the process of reinforcement learning for learning agents. To give human knowledge to learning agent efficiently, it is important to estimate whether or not agents need more knowledge. In this paper, we present our approach to realize efficient teaching on an application which can show the users the progress of learning in a video game.\",\"PeriodicalId\":248901,\"journal\":{\"name\":\"2018 IEEE International Conference on Agents (ICA)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Agents (ICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AGENTS.2018.8459966\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Agents (ICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AGENTS.2018.8459966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Teaching Support to Non-player Learning Agents on Multiplayer Games
Giving human knowledge to learning agents is a good way to speed up the process of reinforcement learning for learning agents. To give human knowledge to learning agent efficiently, it is important to estimate whether or not agents need more knowledge. In this paper, we present our approach to realize efficient teaching on an application which can show the users the progress of learning in a video game.