Theory of Mind > The Naïve Utility Calculus as a unified, quantitative framework for action understanding

This paper presents a formal theory of the Naïve Utility Calculus as a probabilistic generative model, which highlights the role of cost and reward tradeoffs in a Bayesian framework for action-understanding. The model predicts with quantitative accuracy how people infer agents’ subjective costs and rewards based on their observable actions. By distinguishing between desires, goals, and intentions, the model extends to complex action scenarios unfolding over space and time in scenes with multiple objects and multiple action episodes.