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Training plan evolution based on training models

  • Training models have been proposed to model the effect of physical strain on fitness. In this work we explore their use not only for analysis but also to generate training plans to achieve a given fitness goal. These plans have to include side constraints such as, e.g., maximal training loads. Therefore plan generation can be treated as a constraint satisfaction problem and thus can be solved by classical CSP solvers. We show that evolutionary algorithms such as differential evolution or CMA-ES produce comparable results while allowing for more flexibility and requiring less computational resources. Due to this flexibility, it is possible to include well known principles of training science during plan generation, resulting in reasonable training plans.

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Document Type:Conference Object
Author:David Schaefer, Alexander Asteroth, Melanie Ludwig
Parent Title (English):2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA). Madrid, Spain, 2-4 Sept. 2015
Date of first publication:2015/09/28
Departments, institutes and facilities:Fachbereich Informatik
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2015/09/29