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

  • 2,683 Views
  • 2,089 Downloads
  • 8 Citations

Download

Keywords

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