Transfer in Reinforcement Learning Domains

The key contributions of this book are:

• Definition of the transfer problem in RL domains
• Background on RL, sufficient to allow a wide audience to understand discussed transfer concepts
• Taxonomy for transfer methods in RL
• Survey of existing approaches
• In-depth presentation of selected transfer methods
• Discussion of key open questions

By way of the research presented in this book, the author has established himself as the pre-eminent worldwide expert on transfer learning in sequential decision making tasks. A particular strength of the research is its very thorough and methodical empirical evaluation, which Matthew presents, motivates, and analyzes clearly in prose throughout the book. Whether this is your initial introduction to the concept of transfer learning, or whether you are a practitioner in the field looking for nuanced details, I trust that you will find this book to be an enjoyable and enlightening read.

Peter Stone, Associate Professor of Computer Science