Capturing mental state reasoning with influence diagrams
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People have a keen ability to reason about others’ mental states, which is central for communication and cooperation. A core question for cognitive science is what mental representations support this ability. We offer one proposal based on the framework of influence diagrams , an extension of Bayes nets that is suited for representing intentional goal-directed agents. We evaluate this framework in two experiments that require participants to make inferences about what another per- son knows or values. In both experiments, participants’ judgments were better predicted by our influence diagrams account than by several alternative accounts