Ten-month-old infants infer the value of goals from the costs of actions

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  1. Josh Tenenbaum

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Description: Infants understand that people pursue goals, but how do they learn which goals people prefer? Here, we test whether infants solve this problem by inverting a mental model of action planning, trading off the costs of acting against the rewards actions bring. After seeing an agent attain two goals equally often at varying costs, infants expected the agent to prefer the goal it attained through costlier actions. These expectations held across three experiments conveying cost through different physical path features (jump height and width; incline angle), suggesting that an abstract variable, such as ‘force’, ‘work’ or ‘effort’, supported infants’ inferences. We model infants' expectations as Bayesian inferences over utility-theoretic calculations, providing a bridge to recent quantitative accounts of action understanding in older children and adults.

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  • Pre-registration - Gap Width | Registered: 2017-05-17 21:23 UTC

    Liu, tenenbaum, Ullman & 1 more

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