{"title":"深度强化学习概述","authors":"LiChun Cao, ZhiMin","doi":"10.1145/3351917.3351989","DOIUrl":null,"url":null,"abstract":"As a new machine learning method, deep reinforcement learning has made important progress in various fields of people's production and life since it was proposed. However, there are still many difficulties in function design and other aspects. Therefore, further research on deep reinforcement learning is of great significance for promoting the progress of the whole science and society. Based on the basic theory of deep learning, this paper introduces the basic theory, research method, main network model and successful application in various fields of deep reinforcement learning.","PeriodicalId":367885,"journal":{"name":"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"An Overview of Deep Reinforcement Learning\",\"authors\":\"LiChun Cao, ZhiMin\",\"doi\":\"10.1145/3351917.3351989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As a new machine learning method, deep reinforcement learning has made important progress in various fields of people's production and life since it was proposed. However, there are still many difficulties in function design and other aspects. Therefore, further research on deep reinforcement learning is of great significance for promoting the progress of the whole science and society. Based on the basic theory of deep learning, this paper introduces the basic theory, research method, main network model and successful application in various fields of deep reinforcement learning.\",\"PeriodicalId\":367885,\"journal\":{\"name\":\"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3351917.3351989\",\"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 the 2019 4th International Conference on Automation, Control and Robotics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3351917.3351989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
As a new machine learning method, deep reinforcement learning has made important progress in various fields of people's production and life since it was proposed. However, there are still many difficulties in function design and other aspects. Therefore, further research on deep reinforcement learning is of great significance for promoting the progress of the whole science and society. Based on the basic theory of deep learning, this paper introduces the basic theory, research method, main network model and successful application in various fields of deep reinforcement learning.