From information-seeking actions (and their costs), adults jointly infer both whatothers know, and what they believe they can learn
Abstract
We face a challenge when inferring what others know. Actions do not transparently reveal epistemic states: ignorantagents routinely ignore information too costly to obtain, and knowledgeable agents often confirm what they already knowwhen its convenient. We hypothesized that epistemic inferences are sensitive both to agents actions, and the underlyingutilities that best explain them. We tested this possibility in a simple task. Adults watched an explorer decide whetherto collect a map before searching an island for treasure. Participants (n=40) were asked to jointly infer how much theexplorer knew about the treasures location, and how much information the explorer believed the map had. Participantjudgments matched a computational model of epistemic inference structured around an expectation that agents rationallytradeoff information gain with information cost (r=0.86; 95%: 0.740.93, p¡.001). Our results suggest that adult Theory ofMind supports nuanced and graded epistemic inferences from observable action.