Proceedings of the Annual Meeting of the Cognitive Science Society

When we reason about others’ behavior, there are often manyequally-plausible explanations. If Bob climbs a tree to get anapple, we may be unsure if Bob found climbing difficult butreally wanted an apple; if he found climbing easy and was notparticularly excited about the apple; or if he found climbingintrinsically fun and just got the apple because it was conve-nient. Past research suggests that we solve this problem byobtaining repeated observations about the agent and about theworld. Here we argue that, beyond allowing us to sharpen ourinferences about agents and the world, covariation data alsoenables us to do one-shot inferences about novel agents. Weshow that given minimal covariation data, people can infer ob-jective and subjective properties of a new agent from a singleevent. We show that a model that assumes that agents maxi-mize utilities matches participant judgments with quantitativeprecision.