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Escaping Local Views: Discovering Latent Concepts for Interpretable Multi-Agent Reinforcement Learning
Efficient cooperation is challenging due to the usual partial observability of each agent in multi-agent reinforcement learning. Recurrent networks encode local interaction histories, but their hidden representations provide limited insight into the information underlying individual decisions. To ad
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