Acting on the Unseen: Communication-Free Collaborative Filtering for Decentralized Multi-Robot Task Allocation 文章

ArXiv CS.AI2026-05-26NEWSen作者: Alexander Apartsin, Yigal Meshulam, Yehudit Aperstein

摘要

arXiv:2605.25584v1 Announce Type: cross Abstract: Multi-robot task allocation usually assumes some combination of communication, known task models, or a coordinator. We study the opposite extreme, a regime common in practice but overlooked in theory, which we name Zero-Knowledge MRTA (ZK-MRTA): a robot team with no prior knowledge (no task models, not even the latent rank), no communication (no messages, no parameter sharing, no coordinator), and only a partial and privately-noisy view of a public stream of teammates' outcomes. A hidden low-rank structure governs which robot suits which task, and there are far more tasks than rounds, so most (robot, task) pairs are never attempted. Yet each robot can act well on tasks it never attempted, and onboard new tasks, by running online low-rank collaborative filtering over the broadcast (SwarmCF).