Reasoning with Probabilistic and Deterministic Graphical Models

Rina Dechters research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing, and probabilistic reasoning. She is a Chancellors Professor of Computer Science at the University of California, Irvine. She holds a Ph.D. from UCLA, an M.S. degree in applied mathematics from the Weizmann Institute, anda B.S. in mathematics and statistics from the Hebrew University in Jerusalem. She is the author of Constraint Processing published by Morgan Kaufmann (2003), and of Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms published by Morgan and Claypool (2013). She has co-authored close to 200 research papers and has served on the editorial boards of:Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research (JAIR), and Journal of Machine Learning Research (JMLR). She is a Fellow of the American Association of Artificial Intelligence since 1994, was a Radcliffe Fellow during 2005-2006, received the 2007 Association of Constraint Programming (ACP) Research Excellence Award, and became an ACM Fellow in 2013. She was a Co-Editor-in-Chief of Artificial Intelligence from 2011 to 2018 and is the conference chair-elect for IJCAI-2022.

• Preface.- Introduction.- Defining Graphical Models.- Inference: Bucket Elimination for Deterministic Networks.- Inference: Bucket Elimination for Probabilistic Networks.- Tree-Clustering Schemes.- AND/OR Search Spaces for Graphical Models.- Combining Search and Inference: Trading Space for Time.- Conclusion.- Bibliography.- Author's Biography.