arXiv Machine Learning June 16, 2026 By Kale-ab Tessera, Leonard Hinckeldey, Riccardo Zamboni, David Abel, Amos Storkey

Probing Dec-POMDP Reasoning in Cooperative MARL

Read the original on arXiv Machine Learning →

arXiv:2602. 20804v2 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) is typically framed as a decentralised partially observable Markov decision process (Dec-POMDP), a setting whose hardness stems from two key challenges: partial observability and decentralised coordination.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning

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LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning

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