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2018 | OriginalPaper | Chapter

Use of Neural Networks in Q-Learning Algorithm

Authors : Nataliya Boyko, Volodymyr Korkishko, Bohdan Dohnyak, Olena Vovk

Published in: Computer and Information Sciences

Publisher: Springer International Publishing

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Abstract

This article is devoted to the algorithm of training with reinforcement (reinforcement learning). This article will cover various modifications of the Q-Learning algorithm, along with its techniques, which can accelerate learning through the use of neural networks. We also talk about different ways of approximating the tables of this algorithm, consider its implementation in the code and analyze its behavior in different environments. We set the optimal parameters for its implementation, and we will evaluate its performance in two parameters: the number of necessary neural network weight corrections and quality of training.

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Metadata
Title
Use of Neural Networks in Q-Learning Algorithm
Authors
Nataliya Boyko
Volodymyr Korkishko
Bohdan Dohnyak
Olena Vovk
Copyright Year
2018
Book
Computer and Information Sciences

Print ISBN: 978-3-030-00839-0

Electronic ISBN: 978-3-030-00840-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00840-6_21

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