Abstract:Multiagent reinforcement learning (MARL) has been used extensively in the game environment. One of the main challenges in MARL is that the environment of the agent system is dynamic, and the other agents are also updating their strategies. Therefore, modeling the opponents’ learning process and adopting specific strategies to shape learning is an effective way to obtain better training results. Previous studies such as DRON, LOLA and SOS approximated the opponent’s learning process and gave effective applicati… Show more
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