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Promoting Coordination through Policy Regularization in Multi-Agent Reinforcement Learning
Abstract
A central challenge in multi-agent reinforcement learning is the induction of coordination between agents of a team. In this work, we investigate how to promote inter-agent coordination and discuss two possible avenues based respectively on inter-agent modelling and guided synchronized sub-policies. We test each approach in four challen...More
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