Intelligent games meeting with multi-agent deep reinforcement learning: a comprehensive review

被引:0
作者
Wang, Yiqin [1 ]
Wang, Yufeng [1 ]
Tian, Feng [1 ]
Ma, Jianhua [2 ]
Jin, Qun [3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Nanjing, Peoples R China
[2] Hosei Univ, Chiyoda City, Japan
[3] Waseda Univ, Shinjuku City, Japan
关键词
Intelligent game; Multi-agent deep reinforcement learning; Credit assignment; Communications structure; Game simulations; GO; LEVEL; ALGORITHMS; SHOGI; CHESS;
D O I
10.1007/s10462-025-11166-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recent years have witnessed the great achievement of the AI-driven intelligent games, such as AlphaStar defeating the human experts, and numerous intelligent games have come into the public view. Essentially, deep reinforcement learning (DRL), especially multiple-agent DRL (MADRL) has empowered a variety of artificial intelligence fields, including intelligent games. However, there is lack of systematical review on their correlations. This article provides a holistic picture on smoothly connecting intelligent games with MADRL from two perspectives: theoretical game concepts for MADRL, and MADRL for intelligent games. From the first perspective, information structure and game environmental features for MADRL algorithms are summarized; and from the second viewpoint, the challenges in intelligent games are investigated, and the existing MADRL solutions are correspondingly explored. Furthermore, the state-of-the-art (SOTA) MADRL algorithms for intelligent games are systematically categorized, especially from the perspective of credit assignment. Moreover, a comprehensively review on notorious benchmarks are conducted to facilitate the design and test of MADRL based intelligent games. Besides, a general procedure of MADRL simulations is offered. Finally, the key challenges in integrating intelligent games with MADRL, and potential future research directions are highlighted. This survey hopes to provide a thoughtful insight of developing intelligent games with the assistance of MADRL solutions and algorithms.
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页数:53
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