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  A Rational Analysis of the Optimism Bias using Meta-Reinforcement Learning

Schubert, J., Jagadish, A., Binz, M., & Schulz, E. (2023). A Rational Analysis of the Optimism Bias using Meta-Reinforcement Learning. In 2023 Conference on Cognitive Computational Neuroscience (pp. 557-559). doi:10.32470/CCN.2023.1260-0.

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Genre: Konferenzbeitrag

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externe Referenz:
https://2023.ccneuro.org/view_paper.php?PaperNum=1260 (Zusammenfassung)
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Keine Angabe

Urheber

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 Urheber:
Schubert, JA1, Autor           
Jagadish, AK1, Autor                 
Binz, M1, 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: People weigh positive outcomes more heavily than negative ones: a phenomenon commonly referred to as optimism bias. We hypothesized that the optimism bias can emerge as a rational strategy in light of people's experiences. To investigate this, we trained a meta-reinforcement learning agent on an instrumental learning task that elicits the optimism bias. Meta-reinforcement learning agents are known to converge to rational solutions even in complex environments. We analyzed the behavior of converged agents using standard models of reinforcement learning. The results showed that meta-reinforcement learning agents exhibit an optimism bias similar to the one observed in humans. Our findings, therefore, suggest that the optimism bias may be a rational response to people's environments.

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 Datum: 2023-08
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.32470/CCN.2023.1260-0
 Art des Abschluß: -

Veranstaltung

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Titel: Conference on Cognitive Computational Neuroscience (CCN 2023)
Veranstaltungsort: Oxford, UK
Start-/Enddatum: 2023-08-24 - 2023-08-27

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Quelle 1

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Titel: 2023 Conference on Cognitive Computational Neuroscience
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: P-2.37 Start- / Endseite: 557 - 559 Identifikator: -