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A distributional perspective on value function factorization methods for multi-agent reinforcement learning
Conference paper

A distributional perspective on value function factorization methods for multi-agent reinforcement learning

Wei-Fang Sun, Cheng-Kuang Lee and Chun-Yi Lee
Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Vol.3, pp.1659-1661
2021

Abstract

Distributional RL Multi-Agent RL Reinforcement Learning Artificial Intelligence Software Control and Systems Engineering
Distributional reinforcement learning (RL) provides beneficial impacts for the single-agent domain. However, distributional RL methods are not directly compatible with value function factorization methods for multi-agent reinforcement learning. This work provides a distributional perspective on value function factorization, offering a solution for bridging the gap between distributional RL and value function factorization methods.

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