tutorials

The best online AI instructional material that I know. Please tell me if you know any other good stuff! This is one of the most important pages I have, because if you can't get started, you're nowhere.

AI Courses - Giorgio Ingargiola
A comprehensive list. Try this if none of my suggestions on this page are suitable.

artificial intelligence

AIM - Steve Belleguelle
An online course on AI.

An Introduction to the Science of Artificial Intelligence
A web site aimed at students.

MLCOURSE teachpack - Chris Thornton
Formerly published as web pages, this is now available only as postscript. Machine learning for behavior acquisition by a mobile robot. Much of the content relies on the robot only for motivation.

genetic algorithms

Evolutionary Computation FAQ - David Beasley
This ftp directory contains a multi-part "Frequently-Asked Questions" list, including brief explanations of different kinds of genetic algorithms and many references. Check the NEWS file for a table of contents; I can't make a link to it because its name keeps changing. The FAQ is also available in HTML in less-complete form.

An overview of genetic algorithms: Part 1, fundamentals (1993, 16 pages)
David Beasley, David R. Bull, Ralph R. Martin
This compressed postscript paper goes into more detail on how and why GA's work, but doesn't have as many references.

The Genetic Programming Tutorial Notebook - Jaime Fernandez
In genetic programming, the solutions you evolve are themselves computer programs. That's as much power as you can get.

neural networks

Neural Networks FAQ
This "Frequently-Asked Questions" list only has a little tutorial information in it, but it mentions good books and journal articles for beginners.

Neural Nets Course - Kevin Gurney
Lecture notes, homework, software, and other information for a graduate-level neural networks course. It looks self-contained; you should be able to work through the course on your own.

Backpropagator's Review - Don Tveter
A broad review of backpropagation neural networks, with explanations, advice, and information about many variants on the basic algorithm.

reinforcement learning

Background Information for those relatively new to RL
Getting-started links from the Reinforcement Learning Repository. The resources here are unusually good--they include a few tutorials and an entire online book. It will still help if you already know something about machine learning before you try to tackle this subfield.

game theory

Deep understanding of game theory isn't important for most work in machine learning of games, but general knowledge won't hurt.

An Introductory Sketch of Game Theory - Roger A. McCain
By an economist.

Economic and Game Theory - David Levine
The site includes getting-started information and a good collection of links, as well as specialist resources. The emphasis on economics is moderate.