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  Sensorimotor learning and decision-making in complex environments

Braun, D. (2017). Sensorimotor learning and decision-making in complex environments. Talk presented at Kolloquium "Berner Gespräche zur Sportwissenschaft". Bern, Switzerland.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-C5F4-E Version Permalink: http://hdl.handle.net/21.11116/0000-0000-C5F5-D
Genre: Talk

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Braun, D1, 2, 3, Author              
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1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497809              
3Research Group Sensorimotor Learning and Decision-making, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1688138              

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 Abstract: Recent advances in movement neuroscience suggest that sensorimotor control can be considered as a continuous decision-making process in complex environments in which uncertainty and task variability play a key role. Leading theories of motor control assume that the motor system learns probabilistic models and that motor behavior can be explained as the optimization of payoff or cost criteria under the expectation of these models. Here we discuss how the motor system exploits task variability to build up efficient models through structural learning and compare human behavior to Bayes optimal models. In particular, we focus on deviations from these normative models due to effects of model uncertainty and we discuss in how far model uncertainty can be considered as a special case of a general decision-making framework that considers limited information-processing capabilities.

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 Dates: 2017-02-27
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: Braun2017
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Title: Kolloquium "Berner Gespräche zur Sportwissenschaft"
Place of Event: Bern, Switzerland
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Invited: Yes

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