AI RESEARCH
Interference-Aware K-Step Reachable Communication in Multi-Agent Reinforcement Learning
arXiv CS.AI
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ArXi:2603.15054v1 Announce Type: new Effective communication is pivotal for addressing complex collaborative tasks in multi-agent reinforcement learning (MARL). Yet, limited communication bandwidth and dynamic, intricate environmental topologies present significant challenges in identifying high-value communication partners. Agents must consequently select collaborators under uncertainty, lacking a priori knowledge of which partners can deliver task-critical information.