Bayesian Belief Layer for Controllable Opinion Dynamics in LLM Agents

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Bayesian Belief Layer for Controllable Opinion Dynamics in LLM Agents

LLM agents in social simulation revise their opinions implicitly, in context: how open an agent is to persuasion can neither be specified nor verified, and collective outcomes inherit the model's training prior. We introduce Bayesian Chronicle Agents (BCA), a minimal belief layer separating \emph{what} an agent believes from \emph{how} it speaks. Each stance is a probability, updated by one Bayesian step per utterance heard. A single prior-strength parameter $κ$ encodes stubbornness, modeled aft

Source: ArXiv AI