Reinforcement Learning Repository at UMass, Amherst
Background Information for those relatively new to RL
Harmon's illustrated tutorial is a good place to start if you are also
new to the area of Machine Learning. It presents a conceptual framework
- If you are familiar with Machine Learning but are new to RL,
Reinforcement Learning: A Survey
format) by Leslie Kaelbling, Michael Littman, and Andrew Moore
discusses the historical basis of the field, presents a broad
selection of current work, and details the central issues of RL.
- A preview version of an RL textbook, called Reinforcement
Learning, An Introduction is being
written by Richard Sutton and Andrew Barto, and should be available in
published form from MIT Press in December of 1997.
- An article called How to Make
Software Agents Do the Right Thing: An Introduction to Reinforcement
Learning, by Satinder Singh, Peter Norvig, and David Cohn, introduces
RL theory in the context of implementing software agents.
- Glossary of terminology used in RL.
tutorial on hierarchical reinforcement learning and other talks by Tom
Dietterich of Oregon Sate.
POMDPs for Dummies: A tutorial for developing the intuition
behind Partially Observable Markov Decision Processes. From Tony
Cassandra at Brown University.