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  Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty

Nagengast, A., Braun, D., & Wolpert, D. (2010). Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty. PLoS Computational Biology, 6(7), 1-15. doi:10.1371/journal.pcbi.1000857.

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Nagengast, AJ, Autor
Braun, DA1, Autor           
Wolpert, DM, Autor
Affiliations:
1Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, ou_persistent22              

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 Zusammenfassung: Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

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 Datum: 2010-07
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1371/journal.pcbi.1000857
BibTex Citekey: NagengastBW2010
eDoc: e1000857
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Titel: PLoS Computational Biology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 6 (7) Artikelnummer: - Start- / Endseite: 1 - 15 Identifikator: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1