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  4. Reinforcement Learning Applied to a Human Arm Model
 
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2019
Conference Paper
Title

Reinforcement Learning Applied to a Human Arm Model

Abstract
In this contribution, we focus on a muscle actuated human arm model [1] and discuss the applicability of Reinforcement Learning (RL) [2] in order to control it. The content is divided into five sections. We start with the introduction of the human arm model and continue with the optimization method the authors of the model applied. Afterwards, we bring the optimization problem into a form such that RL can handle it and introduce the RL approach we are planning to apply. Before we close with the conclusion, we have a look at the results of the techniques in the numerics section.
Author(s)
Burger, M.
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
Gottschalk, S.
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
Roller, M.
Mainwork
Multibody Dynamics 2019  
Conference
Thematic Conference on Multibody Dynamics 2019  
DOI
10.1007/978-3-030-23132-3_9
Language
English
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
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