Overview
- Nominated by the Rensselaer Polytechnic Institute as an outstanding Ph.D. thesis
- Explains reinforcement learning through a range of problems by exploring what affects reinforcement learning and what contributes to a successful implementation
- Includes a contemporary design of experiments methods, comprising of a novel sequential experimentation procedure that finds convergent learning algorithm parameter subregions and stochastic kriging for response surface metamodeling
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Theses (Springer Theses)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (8 chapters)
Keywords
About this book
Authors and Affiliations
About the author
Christopher Gatti received his PhD in Decision Sciences and Engineering Systems from Rensselaer Polytechnic Institute (RPI). During his time at RPI, his work focused on machine learning and statistics, with applications in reinforcement learning, graph search, stem cell RNA analysis, and neuro-electrophysiological signal analysis. Prior to beginning his graduate work at RPI, he received a BSE in mechanical engineering and an MSE in biomedical engineering, both from the University of Michigan. He then continued to work at the University of Michigan for three years doing computational biomechanics focusing on the shoulder and knee. He has been a gymnast since he was a child and is currently an acrobat for Cirque du Soleil.
Bibliographic Information
Book Title: Design of Experiments for Reinforcement Learning
Authors: Christopher Gatti
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-319-12197-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-12196-3Published: 08 December 2014
Softcover ISBN: 978-3-319-38551-8Published: 22 September 2016
eBook ISBN: 978-3-319-12197-0Published: 22 November 2014
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XIII, 191
Number of Illustrations: 21 b/w illustrations, 25 illustrations in colour
Topics: Computational Intelligence, Logic Design, Artificial Intelligence
Industry Sectors: Aerospace, Automotive, Biotechnology, Chemical Manufacturing, Consumer Packaged Goods, Electronics, Energy, Utilities & Environment, Engineering, Finance, Business & Banking, Health & Hospitals, IT & Software, Law, Materials & Steel, Oil, Gas & Geosciences, Pharma, Telecommunications