An Introduction to Lifted Probabilistic Inference

An Introduction to Lifted Probabilistic Inference - Neural Information Processing Series

Paperback (11 Aug 2021)

  • $91.27
Add to basket

Includes delivery to the United States

10+ copies available online - Usually dispatched within 7 days

Publisher's Synopsis

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.

Book information

ISBN: 9780262542593
Publisher: The MIT Press
Imprint: The MIT Press
Pub date:
DEWEY: 519.2
DEWEY edition: 23
Number of pages: xxii, 429
Weight: 852g
Height: 178mm
Width: 232mm
Spine width: 30mm