- Hardcover: 220 pages
- Publisher: MIT Press (23 Dec 1997)
- Language English
- ISBN-10: 0262041642
- ISBN-13: 978-0262041645
- Product Dimensions: 23.6 x 18.4 x 1.9 cm
- Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: 2,413,002 in Books (See Top 100 in Books)
- See Complete Table of Contents
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"[This] book gives a clear and comprehensive exposition of[the authors] extensive experience in integrating reinforcement learning and autonomous robotics. Their continuing contribution is to the development of a distinct engineering discipline( Behavior engineering') through which such robots can be created. I am excited because their efforts combine some of the best theoretical ideaswith a strong eye for the practical - for what will actually work." Stewart W. Wilson , The Rowland Institute for Science
Product Description
foreword by Lashon Booker To program an autonomous robot to act reliably in a dynamic environment is a complex task. The dynamics of the environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through interaction with its environment and then adapt its behavior, greatly simplifies the designer's work. A learning robot need not be given all of the details of its environment, and its sensors and actuators need not be finely tuned.Robot Shaping is about designing and building learning autonomous robots. The term "shaping" comes from experimental psychology, where it describes the incremental training of animals. The authors propose a new engineering discipline, "behavior engineering," to provide the methodologies and tools for creating autonomous robots. Their techniques are based on classifier systems, a reinforcement learning architecture originated by John Holland, to which they have added several new ideas, such as "mutespec," classifier system "energy," and dynamic population size. In the book they present Behavior Analysis and Training (BAT) as an example of a behavior engineering methodology.
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Format:Hardcover
This books main strength is that it concentrates on the interaction between a human trainer and an artificial learning system. The actual learning system in question is fairly dated now, but doing learning in a robotic environment is a hard task. Their achievement is impressive.
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