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ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration · Around

2024

ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration

Estornell, Andrew, Ton, Jean-Francois, Yao, Yuanshun et al.

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Large language models (LLMs) have demonstrated a remarkable ability to serve as general-purpose tools for various language-based tasks.

Recent works have demonstrated that the efficacy of such models can be improved through iterative dialog between multiple models.
While these paradigms show promise in improving model efficacy, most works in this area treat collaboration as an emergent behavior, rather than a learned behavior.
In doing so, current multi-agent frameworks rely on collaborative behaviors to have been sufficiently trained into off-the-shelf models.

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