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Open AccessArticle

Research and Implementation of Intelligent Decision Based on a Priori Knowledge and DQN Algorithms in Wargame Environment

1
School of Management and Engineering, Nanjing University, Nanjing 210023, China
2
School of Electronics, Computing and Mathematics, University of Derby, Kedleston Rd, Derby DE22 1GB, UK
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Authors to whom correspondence should be addressed.
Electronics 2020, 9(10), 1668; https://doi.org/10.3390/electronics9101668
Received: 28 August 2020 / Revised: 3 October 2020 / Accepted: 6 October 2020 / Published: 13 October 2020
(This article belongs to the Special Issue Deep Reinforcement Learning: Methods and Applications)
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. View Full-Text
Keywords: DQN algorithm; policy modeling; prior knowledge; intelligent decision DQN algorithm; policy modeling; prior knowledge; intelligent decision
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MDPI and ACS Style

Sun, Y.; Yuan, B.; Zhang, T.; Tang, B.; Zheng, W.; Zhou, X. Research and Implementation of Intelligent Decision Based on a Priori Knowledge and DQN Algorithms in Wargame Environment. Electronics 2020, 9, 1668. https://doi.org/10.3390/electronics9101668

AMA Style

Sun Y, Yuan B, Zhang T, Tang B, Zheng W, Zhou X. Research and Implementation of Intelligent Decision Based on a Priori Knowledge and DQN Algorithms in Wargame Environment. Electronics. 2020; 9(10):1668. https://doi.org/10.3390/electronics9101668

Chicago/Turabian Style

Sun, Yuxiang; Yuan, Bo; Zhang, Tao; Tang, Bojian; Zheng, Wanwen; Zhou, Xianzhong. 2020. "Research and Implementation of Intelligent Decision Based on a Priori Knowledge and DQN Algorithms in Wargame Environment" Electronics 9, no. 10: 1668. https://doi.org/10.3390/electronics9101668

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