A tutorial on linear function approximators for dynamic programming and reinforcement learning (Foundations and Trends in Machine Learning): 20

by Alborz Geramifard (Author), Girish Chowdhary (Author), Nicholas Roy (Author), Jonathan P. How (Author), Stefanie Tellex (Author), Thomas J. Walsh (Author)

• New

  Paperback
  2013

  $57.72

  A Markov Decision Process (MDP) is a natural framework for formulating sequential decision-making problems under uncertainty. In recent years, researchers have greatly advanced algorithms for learning and acting in MDPs. This book reviews such algorithms, beginning with well-known dynamic programming methods for solving MDPs.