Literature DB >> 34750584

Latent motives guide structure learning during adaptive social choice.

Jeroen M van Baar1,2, Matthew R Nassar3,4, Wenning Deng1, Oriel FeldmanHall5,6.   

Abstract

Predicting the behaviour of others is an essential part of social cognition. Despite its ubiquity, social prediction poses a poorly understood generalization problem: we cannot assume that others will repeat past behaviour in new settings or that their future actions are entirely unrelated to the past. We demonstrate that humans solve this challenge using a structure learning mechanism that uncovers other people's latent, unobservable motives, such as greed and risk aversion. In four studies, participants (N = 501) predicted other players' decisions across four economic games, each with different social tensions (for example, Prisoner's Dilemma and Stag Hunt). Participants achieved accurate social prediction by learning the stable motivational structure underlying a player's changing actions across games. This motive-based abstraction enabled participants to attend to information diagnostic of the player's next move and disregard irrelevant contextual cues. Participants who successfully learned another's motives were more strategic in a subsequent competitive interaction with that player in entirely new contexts, reflecting that social structure learning supports adaptive social behaviour.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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Year:  2021        PMID: 34750584     DOI: 10.1038/s41562-021-01207-4

Source DB:  PubMed          Journal:  Nat Hum Behav        ISSN: 2397-3374


  37 in total

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  1 in total

Review 1.  The computational challenge of social learning.

Authors:  Oriel FeldmanHall; Matthew R Nassar
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  1 in total

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