期刊
IEEE TRANSACTIONS ON GAMES
卷 12, 期 1, 页码 1-20出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TG.2019.2896986
关键词
Games; Deep learning; Neural networks; Reinforcement learning; Mathematical model; Unsupervised learning; Algorithms; learning; machine learning algorithms; multilayer neural network; artificial intelligence
资金
- Danish Ministry for Higher Education and Science
In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards.
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