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Multi-agent reinforcement learning for character control
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DOI：10.1007/s00371-021-02269-1.png)
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摘要
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Simultaneous control of multiple characters has been a research topic that has been extensively pursued for applications in computer games and computer animations, for applications such as crowd simulation, controlling two characters carrying objects or fighting with one another and controlling a team of characters playing collective sports. With the advance in deep learning and reinforcement learning, there is a growing interest in applying multi-agent reinforcement learning for intelligently controlling the characters to produce realistic movements. In this paper we will survey the state-of-the-art MARL techniques that are applicable for character control. We will then survey papers that make use of MARL for multi-character control and then discuss about the possible future directions of research.
Keyword:
Multi-agent reinforcement learning
Character control
Computer animation
期刊
IF:
2.9
论文数:
4.6K
被引数:
6.5K
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引用论文
AMP: Adversarial Motion Priors for Stylized Physics-Based Character ControlAMP: 基于物理的程式化角色控制的对抗运动先验
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