This is a highly intuitive and accessible introduction to the recent major developments in reinforcement learning, written by two of the field's pioneering contributors.
Dimitri P. Bertsekas and John N. Tsitsiklis, Professors, Department of Electrical Engineering andn Computer Science, Massachusetts Institute of Technology
This book not only provides an introduction to learning theory but also serves as a tremendous source of ideas for further development and applications in the real world.
Toshio Fukuda, Nagoya University, Japan; President, IEEE Robotics and Automantion Society
Reinforcement learning has always been important in the understanding of the driving force behind biological systems, but in the last two decades it has become increasingly important, owing to the development of mathematical algorithms. Barto and Sutton were the prime movers in leading the development of these algorithms and have described them with wonderful clarity in this new text. I predict it will be the standard text.
Dana Ballard, Professor of Computer Science, University of Rochester
The widely acclaimed work of Sutton and Barto on reinforcement learning applies some essentials of animal learning, in clever ways, to artificial learning systems. This is a very readable and comprehensive account of the background, algorithms, applications, and future directions of this pioneering and far-reaching work.
Wolfram Schultz, University of Fribourg, Switzerland
