© 2015

Design of Experiments for Reinforcement Learning


Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Christopher Gatti
    Pages 1-5
  3. Christopher Gatti
    Pages 7-52
  4. Christopher Gatti
    Pages 53-66
  5. Christopher Gatti
    Pages 67-93
  6. Christopher Gatti
    Pages 95-109
  7. Christopher Gatti
    Pages 111-127
  8. Christopher Gatti
    Pages 129-139
  9. Christopher Gatti
    Pages 141-156
  10. Back Matter
    Pages 157-191

About this book


This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.


Kriging Covariance Functions Reinforcement Learning Algorithm Response Surface Metamodeling Sequential CART Stochastic Kriging

Authors and affiliations

  1. 1.Industrial and Systems EngineeringRensselaer Polytechnic InstituteTroyUSA

About the authors

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
  • Series Abbreviated Title Springer Theses
  • DOI
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-12196-3
  • Softcover ISBN 978-3-319-38551-8
  • eBook ISBN 978-3-319-12197-0
  • 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
  • Buy this book on publisher's site