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  Decision-Making with Naturalistic Options

Demircan, C., Pettini, L., Saanum, T., Binz, M., Baczkowski, B., Doeller, C., et al. (2022). Decision-Making with Naturalistic Options. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity (pp. 976-982).

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Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-000A-0829-0 Versions-Permalink: https://hdl.handle.net/21.11116/0000-000B-EFD9-4
Genre: Konferenzbeitrag

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externe Referenz:
https://escholarship.org/content/qt1td8q3wn/qt1td8q3wn.pdf?t=recjjs (Verlagsversion)
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OA-Status:
Keine Angabe

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 Urheber:
Demircan, C1, Autor           
Pettini, L, Autor
Saanum, T1, Autor           
Binz, M1, Autor           
Baczkowski, B, Autor
Doeller, CF, Autor
Garvert, M, Autor
Schulz, E1, Autor           
Affiliations:
1Research Group Computational Principles of Intelligence, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3189356              

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Schlagwörter: -
 Zusammenfassung: How do humans generalise to make better decisions? Previous work has investigated this question using reward-guided decision-making tasks with low-dimensional and artificial stimuli. In this paper, we extend this work by presenting participants with a naturalistic decision-making task, in which options were images of real-world objects and the underlying reward function was based on one of their latent dimensions. Even though participants received no explicit instruction about object features, they quickly learned to do the task and generalised to unseen objects. To understand how they accomplished this, we tested a range of computational models and found that human behaviour is overall best explained by a linear model but that participants’ strategies changed during the experiment. Lastly, we showed that combining pixel-based representations extracted from convolutional neural networks with the original latent dimensions further improved our models. Taken together, our study offers new insights into human decision making under naturalistic settings.

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Sprache(n):
 Datum: 2022-07
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
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Veranstaltung

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Titel: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity
Veranstaltungsort: Toronto, Canada
Start-/Enddatum: 2022-07-27 - 2022-07-30

Entscheidung

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Quelle 1

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Titel: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity
Genre der Quelle: Konferenzband
 Urheber:
Culbertson, J, Herausgeber
Perfors, A, Herausgeber
Rabagliati, H, Herausgeber
Ramenzoni, V, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 976 - 982 Identifikator: ISSN: 1069-7977