An Introduction to Lifted Probabilistic Inference
Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models.
Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field.
After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.
Babak Ahmadi, Hendrik Blockeel, Hung Bui, Yuqiao Chen, Arthur Choi, Adnan Darwiche, Jesse Davis, Rodrigo de Salvo Braz, Pedro Domingos, Daan Fierens, Martin Grohe, Fabian Hadiji, Seyed Mehran Kazemi, Kristian Kersting, Roni Khardon, Angelika Kimmig, Jacek Kisyński, Daniel Lowd, Wannes Meert, Martin Mladenov, Raymond Mooney, Sriraam Natarajan, Mathias Niepert, David Poole, Scott Sanner, Pascal Schweitzer, Nima Taghipour, Guy Van den Broeck
Paperback$70.00 X ISBN: 9780262542593 454 pp. | 7 in x 9 in
“Lifted probabilistic inference is one of the most important directions in contemporary AI, and this book, put together by many of the leading researchers on the topic, provides an excellent overview and a wealth of technical details. This exciting new book will be immensely useful to a broad range of AI researchers and students.”
Holger H. Hoos
AAAI and EurAI Fellow, Universiteit Leiden and University of British Columbia
“What a treat to have many of the leading experts in the field come together to explain the state of the art. Sure to become a standard reference.”
Professor of Artificial Intelligence, University of New South Wales, and Data61