The growth and form of knowledge networks by kinesthetic curiosity.


Journal

Current opinion in behavioral sciences
ISSN: 2352-1546
Titre abrégé: Curr Opin Behav Sci
Pays: Netherlands
ID NLM: 101644944

Informations de publication

Date de publication:
Oct 2020
Historique:
entrez: 6 8 2021
pubmed: 7 8 2021
medline: 7 8 2021
Statut: ppublish

Résumé

Throughout life, we might seek a calling, companions, skills, entertainment, truth, self-knowledge, beauty, and edification. The practice of curiosity can be viewed as an extended and open-ended search for valuable information with hidden identity and location in a complex space of interconnected information. Despite its importance, curiosity has been challenging to computationally model because the practice of curiosity often flourishes without specific goals, external reward, or immediate feedback. Here, we show how network science, statistical physics, and philosophy can be integrated into an approach that coheres with and expands the psychological taxonomies of specific-diversive and perceptual-epistemic curiosity. Using this interdisciplinary approach, we distill functional modes of curious information seeking as searching movements in information space. The kinesthetic model of curiosity offers a vibrant counterpart to the deliberative predictions of model-based reinforcement learning. In doing so, this model unearths new computational opportunities for identifying what makes curiosity curious.

Identifiants

pubmed: 34355045
doi: 10.1016/j.cobeha.2020.09.007
pmc: PMC8330694
mid: NIHMS1683568
doi:

Types de publication

Journal Article

Langues

eng

Pagination

125-134

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH112847
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS099348
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH107235
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC009209
Pays : United States
Organisme : NIMH NIH HHS
ID : R21 MH106799
Pays : United States
Organisme : NIDA NIH HHS
ID : K01 DA047417
Pays : United States
Organisme : NICHD NIH HHS
ID : R01 HD086888
Pays : United States

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Auteurs

Dale Zhou (D)

Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

David M Lydon-Staley (DM)

Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania.
Annenberg School for Communication, University of Pennsylvania.
Leonard Davis Institute of Health Economics, University of Pennsylvania.

Perry Zurn (P)

Department of Philosophy & Religion, American University, Washington, D.C.

Danielle S Bassett (DS)

Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania.
Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania.
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania.
Department of Neurology, Perelman School of Medicine, University of Pennsylvania.
Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania.
Santa Fe Institute, Santa Fe, NM 87501 USA.

Classifications MeSH