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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Counterfactual Multi-Agent Policy Gradients

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Jakob Foerster

University of Oxford


Gregory Farquhar

University of Oxford


Triantafyllos Afouras

University of Oxford


Nantas Nardelli

University of Oxford


Shimon Whiteson

University of Oxford


DOI:

10.1609/aaai.v32i1.11794


Abstract:

Many real-world problems, such as network packet routing and the coordination of autonomous vehicles, are naturally modelled as cooperative multi-agent systems. There is a great need for new reinforcement learning methods that can efficiently learn decentralised policies for such systems. To this end, we propose a new multi-agent actor-critic method called counterfactual multi-agent (COMA) policy gradients. COMA uses a centralised critic to estimate the Q-function and decentralised actors to optimise the agents' policies. In addition, to address the challenges of multi-agent credit assignment, it uses a counterfactual baseline that marginalises out a single agent's action, while keeping the other agents' actions fixed. COMA also uses a critic representation that allows the counterfactual baseline to be computed efficiently in a single forward pass. We evaluate COMA in the testbed of StarCraft unit micromanagement, using a decentralised variant with significant partial observability. COMA significantly improves average performance over other multi-agent actor-critic methods in this setting, and the best performing agents are competitive with state-of-the-art centralised controllers that get access to the full state.

Topics: AAAI

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HOW TO CITE:

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson Counterfactual Multi-Agent Policy Gradients Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson Counterfactual Multi-Agent Policy Gradients AAAI 2018, .

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson (2018). Counterfactual Multi-Agent Policy Gradients. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. Counterfactual Multi-Agent Policy Gradients. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. 2018. Counterfactual Multi-Agent Policy Gradients. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. (2018) "Counterfactual Multi-Agent Policy Gradients", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson, "Counterfactual Multi-Agent Policy Gradients", AAAI, p., 2018.

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. "Counterfactual Multi-Agent Policy Gradients". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. "Counterfactual Multi-Agent Policy Gradients". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Jakob Foerster||Gregory Farquhar||Triantafyllos Afouras||Nantas Nardelli||Shimon Whiteson. Counterfactual Multi-Agent Policy Gradients. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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