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  Tracking the Unknown: Modeling Long-Term Implicit Skill Acquisition as Non-Parametric Bayesian Sequence Learning

Elteto, N., Nemeth, D., Janacsek, K., & Dayan, P. (2021). Tracking the Unknown: Modeling Long-Term Implicit Skill Acquisition as Non-Parametric Bayesian Sequence Learning. Poster presented at 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria.

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Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-0008-E403-3 Versions-Permalink: https://hdl.handle.net/21.11116/0000-000A-E9F3-D
Genre: Poster

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externe Referenz:
https://cognitivesciencesociety.org/wp-content/uploads/2021/07/CSSPosterListingJuly15.pdf (Zusammenfassung)
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 Urheber:
Elteto, N1, 2, Autor           
Nemeth, D, Autor
Janacsek, K, Autor
Dayan, P1, 2, Autor           
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

Inhalt

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Schlagwörter: -
 Zusammenfassung: Long perceptuo-motor sequences underlie skills from walking to language learning, and are often learned gradually and
unconsciously in the face of noise. We used a non-parametric Bayesian n-gram model (Teh, 2006) to characterize the
multi-day evolution of human subjects’ implicit representation of a serial reaction time task sequence with second-order
contingencies. The reaction time for an element in the sequence depended on zero, one and more preceding elements
at the same time, predicting frequency, repetition and higher-order learning effects. Our trial-level dynamic model
captured these coexistent facilitation effects by seamlessly combining information from shorter and longer windows
onto past events. We show how shifting their priors over window lengths allowed subjects to grow and refine their
internal sequence representations week by week.

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 Datum: 2021-072021-11
 Publikationsstatus: Erschienen
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Veranstaltung

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Titel: 43rd Annual Conference of the Cognitive Science Society (CogSci 2021)
Veranstaltungsort: Wien, Austria
Start-/Enddatum: 2021-07-26 - 2021-07-29

Entscheidung

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Projektinformation

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Quelle 1

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Titel: 43rd Annual Conference of the Cognitive Science Society (CogSci 2021): Workshop 2 Using Games to Understand Intelligence
Genre der Quelle: Konferenzband
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Affiliations:
Ort, Verlag, Ausgabe: Red Hook, NY, USA : Curran
Seiten: - Band / Heft: - Artikelnummer: 1-C-105 Start- / Endseite: 3307 Identifikator: ISBN: 978-1-7138-3525-7