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Active Inference For Self-organizing Multi-llm Systems: A Bayesian Thermodynamic Approach To Adaptation

Abstract

This paper introduces a novel approach to creating adaptive language agents by integrating active inference with large language models (LLMs). While LLMs demonstrate remarkable capabilities, their reliance on static prompts limits adaptation to new information and changing environments. We address this by implementing an active inference framework that acts as a cognitive layer above an LLM-based

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