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An excellent introduction to Reinforcement Learning
am 1. März 2000
This is probably one of the best book I have read in the past 1 year.
The authors present the subject with an excellent balance of mathematical, computational and intuitive material. The book also includes plenty of real-life examples to explain the concepts and motivations for the algorithms.
The book starts with examples and intuitive introduction and definition of reinforcement learning. It follows with 3 chapters on the 3 fundamental approaches to reinforcement learning: Dynamic programming, Monte Carlo and Temporal Difference methods. Subsequent chapters build on these methods to generalize to a whole spectrum of solutions and algorithms.
The book is very readable by average computer students. Possibly the only difficult one is chapter 8, which deals with some neural network concepts.
I highly recommend this book to anyone who wants to learn about this subject.