The undershoot bias: learning to act optimally under uncertainty.

Full Abstract

Learning in stochastic environments is increasingly viewed as an important psychological ability. To extend these results from a perceptual to a motor domain, we tested whether participants could learn to solve a stochastic minimal-time task using exploratory learning. The task involved moving a cursor on a computer screen to a target. We systematically varied the degree of random error in movement in three different conditions; each condition had a distinct time-optimal solution. We found that participants approximated the optimal solutions with practice. The results show that adults are sensitive to the stochastic structure of a task and naturally adjust the magnitude of an undershoot bias to the particular movement error of a task.

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Author information

Author/s: Engelbrecht, Sascha E (SE); Berthier, Neil E (NE); O'Sullivan, Laura P (LP);

Affiliation: University of Massachusetts, Amherst 01003, USA.

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.

Journal: Psychological science : a journal of the American Psychological Society / APS (Psychol Sci), published in United States. (Language: eng)

Reference: 2003-May; vol 14 (issue 3) : pp 257-61

Dates: Created 2003/05/13; Completed 2003/08/05; Revised 2006/11/15;

PMID: 12741750, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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