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Bayesian Belief Layer for Controllable Opinion Dynamics in LLM Agents

[cs.MA] Autorzy: Hafsa Akbar, Daniel Platnick, Marjan Alirezaie i 1 więcej

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 after its role in Friedkin--Johnsen (FJ) opinion dynamics. We then sweep this parameter to yield three canonical regimes of opinion dynamics on demand (consensus, persistent disagreement, committed-minority influence), with persistent disagreement matching the FJ closed-form fixed points at $R^2\!=\!0.93$--$0.99$. We further show that prescribed $κ$ remains recoverable after the language round-trip,…

Kategoria arxiv
cs.MA
Kategoria
cs.MA
Pdf
https://arxiv.org/pdf/2609.21997v1

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