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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Reinforcement Learning for Robotic Soccer Playing
 Brychta, Adam ; Švec, Tomáš (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to create a reinforcement learning agent that is able to play a soccer. I'm working with the deep Q-learning algorithm, which uses deep neural network. The practical part of this work is about implementing the agent for reinforcement learning. The goal of the agent is to choose the best action possible for a given situation. The agent is being trained in a variety of scenarios. The result of this thesis shows an approach to control soccer player using machine learning.
Detailed record
Posilované učení a agentní prostředí
 Brychta, Adam
This work deals with reinforcement learning and its application in an agent environment. The theoretical part includes an analysis of the theory covering areas of agent environments, neural networks and reinforcement learning. The practical part is focused on the design and implementation of a deep reinforcement learning agent with the possibility of using hierarchical reinforcement learning.
Detailed record
Reinforcement Learning for Robotic Soccer Playing
 Brychta, Adam ; Švec, Tomáš (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to create a reinforcement learning agent that is able to play a soccer. I'm working with the deep Q-learning algorithm, which uses deep neural network. The practical part of this work is about implementing the agent for reinforcement learning. The goal of the agent is to choose the best action possible for a given situation. The agent is being trained in a variety of scenarios. The result of this thesis shows an approach to control soccer player using machine learning.
Detailed record

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