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by Kardi Teknomo
In this tutorial, you will discover step by step how an agent learns through training without teacher (unsupervised) in unknown environment. You will find out part of reinforcement learning algorithm called Q-learning. Reinforcement learning algorithm has been widely used for many applications such as robotics, multi agent system, game, motion planning, navigation, and etc.
Instead of learning the theory of reinforcement that you can read it from many books and other web sites (see Resources for more references), this tutorial will introduce the concept through simple but comprehensive numerical examples. If you purchase the e-book of this tutorial, you will also receive the companion worksheet and the matlab files.
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Let us start the tutorial (clicks the topic below).
Modeling the Environment
Agent, State and Action Introduction
Q Learning
Q Learning Algorithm
Numerical Example
Another Q learning Example: Tower of Hanoi
Q-Learning Solution for Tower of Hanoi
Q Learning using Matlab
Q Learning using MS Excel
Practice make perfect
Resources
Click here to purchase the complete E-book of this tutorial
Send your feedback and comments for this tutorial
This tutorial is copyrighted.
Preferable reference for this tutorial is
Teknomo, Kardi. 2005. Q-Learning by Examples. http://people.revoledu.com/kardi/tutorial/ReinforcementLearning/index.html
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