Design of Experiments for Reinforcement Learning (Springer Theses)

Christopher Gatti

  • 出版商: Springer
  • 出版日期: 2014-12-08
  • 售價: $4,330
  • 貴賓價: 9.5$4,114
  • 語言: 英文
  • 頁數: 191
  • 裝訂: Hardcover
  • ISBN: 3319121960
  • ISBN-13: 9783319121963
  • 相關分類: ReinforcementDeepLearning
  • 海外代購書籍(需單獨結帳)

商品描述

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.