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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

Seek of an Optimal Way by Q-Learning

Y. Dahmani and A. Benyettou

Abstract

In this article, we presented the Q-Learning training method which is a derivative of the reinforcement learning called sometimes training by penalty-reward. We illustrate this by an application to the mobility of a mobile in an enclosure closed on the basis of a starting point towards an unspecified arrival point. The objective is to find an optimal way optimal without leaving the enclosure.

Journal of Computer Science
Volume 1 No. 1, 2005, 28-30

DOI: https://doi.org/10.3844/jcssp.2005.28.30

Submitted On: 9 May 2005 Published On: 31 March 2005

How to Cite: Dahmani, Y. & Benyettou, A. (2005). Seek of an Optimal Way by Q-Learning. Journal of Computer Science, 1(1), 28-30. https://doi.org/10.3844/jcssp.2005.28.30

Open AccessCopyright: © 2005 Y. Dahmani and A. Benyettou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Reinforcement Learning
  • Q-Learning
  • Exploration Phase
  • Exploitation Phase