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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. You may also download the Matlab code or MS Excel Spreadsheet for free.
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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 (download free worksheet here)
Q-Learning Solution for Tower of Hanoi
Q Learning using Matlab (free code)
Q Learning using MS Excel (download free worksheet here)
Practice make perfect
Resources
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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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