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Flexible social inference facilitates targeted social learning when rewards are not observable.
Hawkins, Robert D; Berdahl, Andrew M; Pentland, Alex 'Sandy'; Tenenbaum, Joshua B; Goodman, Noah D; Krafft, P M.
Afiliação
  • Hawkins RD; Department of Psychology, Stanford University, Stanford, CA, USA. rdhawkins@wisc.edu.
  • Berdahl AM; Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA. rdhawkins@wisc.edu.
  • Pentland A'; School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA.
  • Tenenbaum JB; MIT Media Lab, MIT, Cambridge, MA, USA.
  • Goodman ND; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
  • Krafft PM; Department of Psychology, Stanford University, Stanford, CA, USA.
Nat Hum Behav ; 7(10): 1767-1776, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37591983
ABSTRACT
Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others' underlying knowledge and success from observable trajectories of behaviour. We compared our social inference model against simpler heuristics in three studies of human behaviour in a collective-sensing task. Experiment 1 demonstrated that average performance improved as a function of group size at a rate greater than predicted by heuristic models. Experiment 2 introduced artificial agents to evaluate how individuals selectively rely on social information. Experiment 3 generalized these findings to a more complex reward landscape. Taken together, our findings provide insight into the relationship between individual social cognition and the flexibility of collective behaviour.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Hum Behav Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Hum Behav Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos