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arXiv Machine Learning By Ziqing Zhou, Linqiang Hu, Yuning Chen, Hongda Zhang, Zhao Huang, Ding Zhou, Haining Xu

Collective Collaboration of Recursive Autonomous Agents

Read the original on arXiv Machine Learning →

The paper proposes a framework for the collective collaboration of recursive autonomous agents (RAAs) in smart factories. It introduces a common task and capability interface that enables recursive decomposition of production objectives from the top down and aggregation of conditional capabilities from the bottom up. The framework includes organizational models for leaf and composite units, conditions for finite task expansion, and operational mechanisms linking task decomposition, resource commitments, result aggregation, and coordination across changing production conditions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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