New Formal Framework Proposed for How Minds Infer Others' Beliefs
A new preprint introduces the Theory of Mind Utility (ToM-U), a formal computational framework specifying how agents infer the epistemic states of others by tracking information access histories and credibility. The model constructs directed graph structures called Local Epistemic World Models (LEWMs) and evaluates them against observed behavior, distinguishing itself from existing Bayesian and simulation-based accounts. The work aims to provide a domain-agnostic, falsifiable foundation for social cognition research and AI systems that must reason about other agents' beliefs.
Nikolos Gurney's preprint, submitted to arXiv in June 2026, presents the Theory of Mind Utility (ToM-U) as a computational-level formalization of mentalizing — the cognitive process of inferring what others believe. Rather than presupposing belief states as prior Bayesian Theory of Mind models do, ToM-U derives them by building Local Epistemic World Models (LEWMs), which are directed typed graphs encoding agents, informational states, and the ordered, credibility-weighted history of who learned what and when. Five formal definitions specify the model's structure, including a bounded recursion mechanism for higher-order mentalizing (e.g., beliefs about beliefs) and a residue function that records structured traces of failed inference attempts. The framework generates directional, falsifiable predictions about when and why mentalizing breaks down, grounded in the model's structural properties rather than added assumptions. By operating upstream of goal inference and other social cognitive processes, ToM-U is positioned as a general mechanism applicable across both cognitive science and artificial intelligence contexts.
What's missing
As a preprint, ToM-U has not yet undergone peer review. The paper is primarily a theoretical proposal; it does not report empirical validation of the model's predictions against human behavioral data or AI benchmarks. Key open questions include whether the LEWM evaluation procedure scales tractably with the number of agents and recursion depth, and how the bounded proliferation mechanism's parameters are set or learned in practice.
What different sources said
- arXiv cs.AICenter
The Theory of Mind Utility: Formal Specification of a Mentalizing Mechanism
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