LAC-MAS is a trajectory-driven framework in which LLMs supply high-level guidance to shape both agent-internal behaviors and external cooperation patterns for improved distributed black-box consensus optimization.
Proceedings of the 41st International Conference on Machine Learning , pages =
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Learning to Act and Cooperate for Distributed Black-Box Consensus Optimization
LAC-MAS is a trajectory-driven framework in which LLMs supply high-level guidance to shape both agent-internal behaviors and external cooperation patterns for improved distributed black-box consensus optimization.