Algorithms for Reinforcement Learning

Csaba Szepesvári received his PhD in 1999 from "Jozsef Attila" University, Szeged, Hungary. He is currently an Associate Professor at the Department of Computing Science of the University of Alberta and a principal investigator of the Alberta Ingenuity Center for Machine Learning. Previously, he held a senior researcher position at the Computer and Automation Research Institute of the Hungarian Academy of Sciences, where he headed the Machine Learning Group. Before that, he spent 5 years in the software industry. In 1998, he became the Research Director of Mindmaker, Ltd., working on natural language processing and speech products, while from 2000, he became the Vice President of Research at the Silicon Valley company Mindmaker Inc. He is the coauthor of a book on nonlinear approximate adaptive controllers, published over 80 journal and conference papers and serves as the Associate Editor of IEEE Transactions on Adaptive Control and AI Communications, is on the board of editors of theJournal of Machine Learning Research and the Machine Learning Journal, and is a regular member of the program committee at various machine learning and AI conferences. His areas of expertise include statistical learning theory, reinforcement learning and nonlinear adaptive control.

• Markov Decision Processes.- Value Prediction Problems.- Control.- For Further Exploration.