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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning

February 1, 2023

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Authors

Chao Wen

Nanjing University of Aeronautics and Astronautics


Xinghu Yao

Nanjing University of Aeronautics and Astronautics


Yuhui Wang

Nanjing University of Aeronautics and Astronautics


Xiaoyang Tan

Nanjing University of Aeronautics and Astronautics


DOI:

10.1609/aaai.v34i05.6223


Abstract:

This work presents a sample efficient and effective value-based method, named SMIX(λ), for reinforcement learning in multi-agent environments (MARL) within the paradigm of centralized training with decentralized execution (CTDE), in which learning a stable and generalizable centralized value function (CVF) is crucial. To achieve this, our method carefully combines different elements, including 1) removing the unrealistic centralized greedy assumption during the learning phase, 2) using the λ-return to balance the trade-off between bias and variance and to deal with the environment's non-Markovian property, and 3) adopting an experience-replay style off-policy training. Interestingly, it is revealed that there exists inherent connection between SMIX(λ) and previous off-policy Q(λ) approach for single-agent learning. Experiments on the StarCraft Multi-Agent Challenge (SMAC) benchmark show that the proposed SMIX(λ) algorithm outperforms several state-of-the-art MARL methods by a large margin, and that it can be used as a general tool to improve the overall performance of a CTDE-type method by enhancing the evaluation quality of its CVF. We open-source our code at: https://github.com/chaovven/SMIX.

Topics: AAAI

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HOW TO CITE:

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning Proceedings of the AAAI Conference on Artificial Intelligence (2020) 7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning AAAI 2020, 7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan (2020). SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. 2020. SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning. "Proceedings of the AAAI Conference on Artificial Intelligence". 7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. (2020) "SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning", Proceedings of the AAAI Conference on Artificial Intelligence, p.7301-7308

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan, "SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning", AAAI, p.7301-7308, 2020.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. "SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. "SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 7301-7308.

Chao Wen||Xinghu Yao||Yuhui Wang||Xiaoyang Tan. SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning. AAAI[Internet]. 2020[cited 2023]; 7301-7308.


ISSN: 2374-3468


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