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20192026
most citedPromoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning

14 citations · 31 across the 7 of their papers we have counts for

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Showing 2023Show all

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cs.LG2023★ 1 cited

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

Paul Barde, Jakob Foerster, Derek Nowrouzezahrai +1

Training multiple agents to coordinate is an essential problem with applications in robotics, game theory, economics, and social sciences. However, most existing Multi-Agent Reinfo…