LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning

NeurIPS 2019 Yali DuLei HanMeng FangJi LiuTianhong DaiDacheng Tao

A great challenge in cooperative decentralized multi-agent reinforcement learning (MARL) is generating diversified behaviors for each individual agent when receiving only a team reward. Prior studies have paid much effort on reward shaping or designing a centralized critic that can discriminatively credit the agents... (read more)

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