Q-Learning By Examples: Resources

Resources on Reiforcement Learning

INTRODUCTION & TUTORIAL

Reinforcement Learning by Sutton and Barto
Reinforcement Learning by Dayan and Watkins
Temporal Difference Learning and TD-Gammon By Gerald Tesauro (classical paper mark the success of RL)
Reinforcement Learning: A Survey by Leslie Pack Kaelbling, Michael L. Littman and Andrew W. Moore
Extending Q-Learning to General Adaptive Multi-Agent Systems by Gerald Tesauro
Mark Humphrys dissertation contain how Q learning work, discrete Q learning
Geri Tesauro Multi Agent Learning Mini Tutorial (PPT)
Colorado State Univ Reinforcement Learning and Control
Teknomo tutorial on Simple learning
Salsa Introduction to Reinforcement Learning

ARTICLES

Bayesian Q Learning by R. Dearden, N. Friedman, and S. Russell
Multigrid Q-Learning by Charles W. Anderson and Stewart G. Crawford-Hines
Improving Generalisation for Temporal Difference Learning: The Successor Representation by Peter Dayan
Reinforcement Learning for Stochastic Cooperative Multi-Agent-Systems by Martin Lauer and Martin Riedmiller
Feudal Reinforcement Learning by Peter Dayan and Geoffrey E Hinton
A New Q-Learning Algorithm Based on the Metropolis Criterion by Maozu Guo, Yang Liu, and Jacek Malec

APPLICATIONS

Oil Market Modeling Using Q-Learning by Michael Wunder
Pricing in agent economies using multi-agent Q-learning by Gerald Tesauro and Jeffrey O. Kephart
Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions by Manu Sridharan and Gerald J. Tesauro
Reinforcement Learning and its Application to Othello by Nees Jan van Eck, Michiel van Wezel
Reinforcement Learning applied to a Radar Tracking Task
Car Simulation Using Reinforcement Learning by Zhijin Wang

SOFTWARE & CODE

Q-LEARNING

OTHER EXCELLENT RESOURCES

Books (references)

Mitchell, T. M. (1997) Machine Learning, McGrawHill
Sutton, R.S. and Barto, A.G. (1998), Reinforcement Learning an Introduction, MIT Press