Everyday social interactions are heavily influenced by our snap judgments about others ’ goals. Even young infants can infer the goals of intentional agents from observing how they interact with objects and other agents in their environment: e.g., that one agent is ‘helping ’ or ‘hindering ’ another’s attempt to get up a hill or open a box. We propose a model for how people can infer these social goals from actions, based on inverse planning in multiagent Markov decision problems (MDPs). The model infers the goal most likely to be driving an agent’s behavior by assuming the agent acts approximately rationally given environmental constraints and its model of other agents present. We also present behavioral evidence in support of this model over a simpler, perceptual cue-based alternative. 1

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People are amateur social psychologists: they explain other people’s behavior, infer what other people are thinking and feeling, and predict how other people will act. I will refer to this sort of psychologizing as social reasoning in order to highlight the fact that it involves reasoning about people. Social reasoning often requires significant leaps of inductive inference: people infer others ’ mental states, such as their preferences, goals, and beliefs, from relatively sparse information, such as others ’ choices and actions. The capacity to reason about mental states and about how mental states relate to behavior is often referred