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. Electronics2020, 9, 1668.
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.
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. Electronics2020, 9, 1668.
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.
Abstract
The reinforcement learning problem of complex action control in the Multi-player wargame is a hot research topic in recent years. In this paper , a game system based on turn-based confrontation is designed and implemented with the state-of-the-art deep reinforcement learning models. Specifically, we first design a Q-learning algorithm to achieve intelligent decision-making, which is based the DQN(Deep Q Network) to model the complex game behaviors. Then, 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 is validated and its performance surpass 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.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
