Seek of an Optimal Way by Q-Learning
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.
DOI: https://doi.org/10.3844/jcssp.2005.28.30
Copyright: © 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