Research and implementation of intelligent decision based on a priori knowledge and DQN algorithms in wargame environment

Journal article


Sun, Yuxiang, Yuan, Bo, Zhang, Tao, Tang, Bojian, Zheng, Wanwen and Zhou, Xianzhong 2020. Research and implementation of intelligent decision based on a priori knowledge and DQN algorithms in wargame environment. Electronics. 9 (10), p. 1668. https://doi.org/10.3390/electronics9101668
AuthorsSun, Yuxiang, Yuan, Bo, Zhang, Tao, Tang, Bojian, Zheng, Wanwen and Zhou, Xianzhong
Abstract

The reinforcement learning problem of complex action control in a multi-player wargame has been a hot research topic in recent years. In this paper, a game system based on turn-based confrontation is designed and implemented with state-of-the-art deep reinforcement learning models. Specifically, we first design a Q-learning algorithm to achieve intelligent decision-making, which is based on the DQN (Deep Q Network) to model complex game behaviors. Then, an a priori knowledge-based algorithm PK-DQN (Prior Knowledge-Deep Q Network) is introduced to improve the DQN algorithm, which accelerates the convergence speed and stability of the algorithm. The experiments demonstrate the correctness of the PK-DQN algorithm, it is validated, and its performance surpasses the conventional DQN algorithm. Furthermore, the PK-DQN algorithm shows effectiveness in defeating the high level of rule-based opponents, which provides promising results for the exploration of the field of smart chess and intelligent game deduction

KeywordsDQN algorithm; policy modeling; prior knowledge; intelligent decision
Year2020
JournalElectronics
Journal citation9 (10), p. 1668
PublisherMDPI AG
ISSN2079-9292
Digital Object Identifier (DOI)https://doi.org/10.3390/electronics9101668
Web address (URL)http://hdl.handle.net/10545/625346
http://creativecommons.org/licenses/by-nc-sa/4.0/
hdl:10545/625346
Publication dates13 Oct 2020
Publication process dates
Deposited06 Nov 2020, 11:34
Accepted06 Oct 2020
Rights

Attribution-NonCommercial-ShareAlike 4.0 International

ContributorsUniversity of Derby and Nanjing University, China
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