Review of Adversarial Game Techniques Based on Multi-Agent Reinforcement Learning
Multi-agent adversarial systems are complex multi-perty game systems,and in recent years,many studies have focused on using reinforcement learning to solve multi-agent adversarial game problems.This article reviews intelligent game adversarial algorithms from the perspective of multi-agent reinforcement learning.First,a brief introduction to multi-agent reinforcement learning and game theory is given;then,four key technical difficulties of multi-agent reinforce-ment learning are proposed,and related solutions are sorted out;finally,the frontier research direction of multi-agent rein-forcement learning is summarized,and three research hotspots and challenges are concluded.This review lays a founda-tion for the subsequent research and provides ideas for solving the game antagonism problem by using multi-agent rein-forcement learning.
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维普
