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Hluboké posilovaná učení a řešení pohybu robotu typu had / Deep reinforcement learning and snake-like robot locomotion design

This master thesis is discussing application of reinforcement learning in deep learning tasks. In theoretical part, basics about artificial neural networks and reinforcement learning. The thesis describes theoretical model of reinforcement learning process - Markov processes. Some interesting techniques are shown on conventional reinforcement learning algorithms. Some of widely used deep reinforcement learning algorithms are described here as well. Practical part consist of implementing model of robot and it's environment and of the deep reinforcement learning system itself.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:416652
Date January 2020
CreatorsKočí, Jakub
ContributorsDobrovský, Ladislav, Matoušek, Radomil
PublisherVysoké učení technické v Brně. Fakulta strojního inženýrství
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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