An overview on algorithms and applications of deep reinforcement learning
Deep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy...
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| Format: | Article |
| Language: | zho |
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POSTS&TELECOM PRESS Co., LTD
2020-12-01
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| Series: | 智能科学与技术学报 |
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| Online Access: | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202034 |
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| _version_ | 1846171127031791616 |
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| author | Zhaoyang LIU Chaoxu MU Changyin SUN |
| author_facet | Zhaoyang LIU Chaoxu MU Changyin SUN |
| author_sort | Zhaoyang LIU |
| collection | DOAJ |
| description | Deep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy gradient as well as related developed algorithms.In addition, the applications of DRL in video games, navigation, multi-agent cooperation and recommendation field were intensively reviewed.Finally, a prospect for the future research of DRL was made, and some research suggestions were given. |
| format | Article |
| id | doaj-art-86d54b026a904c00b82eb57191c12874 |
| institution | Kabale University |
| issn | 2096-6652 |
| language | zho |
| publishDate | 2020-12-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 智能科学与技术学报 |
| spelling | doaj-art-86d54b026a904c00b82eb57191c128742024-11-11T06:52:10ZzhoPOSTS&TELECOM PRESS Co., LTD智能科学与技术学报2096-66522020-12-01231432659638255An overview on algorithms and applications of deep reinforcement learningZhaoyang LIUChaoxu MUChangyin SUNDeep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy gradient as well as related developed algorithms.In addition, the applications of DRL in video games, navigation, multi-agent cooperation and recommendation field were intensively reviewed.Finally, a prospect for the future research of DRL was made, and some research suggestions were given.http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202034artificial intelligence;deep reinforcement learning;value function;policy gradient;navigation;cooperation;complex environment;generalization;robustness |
| spellingShingle | Zhaoyang LIU Chaoxu MU Changyin SUN An overview on algorithms and applications of deep reinforcement learning 智能科学与技术学报 artificial intelligence;deep reinforcement learning;value function;policy gradient;navigation;cooperation;complex environment;generalization;robustness |
| title | An overview on algorithms and applications of deep reinforcement learning |
| title_full | An overview on algorithms and applications of deep reinforcement learning |
| title_fullStr | An overview on algorithms and applications of deep reinforcement learning |
| title_full_unstemmed | An overview on algorithms and applications of deep reinforcement learning |
| title_short | An overview on algorithms and applications of deep reinforcement learning |
| title_sort | overview on algorithms and applications of deep reinforcement learning |
| topic | artificial intelligence;deep reinforcement learning;value function;policy gradient;navigation;cooperation;complex environment;generalization;robustness |
| url | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202034 |
| work_keys_str_mv | AT zhaoyangliu anoverviewonalgorithmsandapplicationsofdeepreinforcementlearning AT chaoxumu anoverviewonalgorithmsandapplicationsofdeepreinforcementlearning AT changyinsun anoverviewonalgorithmsandapplicationsofdeepreinforcementlearning AT zhaoyangliu overviewonalgorithmsandapplicationsofdeepreinforcementlearning AT chaoxumu overviewonalgorithmsandapplicationsofdeepreinforcementlearning AT changyinsun overviewonalgorithmsandapplicationsofdeepreinforcementlearning |