Luc De Raedt: Statistical Relational Artificial Intelligence, Gebunden
Statistical Relational Artificial Intelligence
- Logic, Probability, and Computation
(soweit verfügbar beim Lieferanten)
- Verlag:
- Springer Nature Switzerland, 03/2016
- Einband:
- Gebunden, HC runder Rücken kaschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783031000225
- Artikelnummer:
- 10970586
- Umfang:
- 192 Seiten
- Gewicht:
- 565 g
- Maße:
- 241 x 196 mm
- Stärke:
- 16 mm
- Erscheinungstermin:
- 24.3.2016
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.
Biografie (David Poole)
David Poole is a Professor of Computer Science at the University of British Columbia. He is known for his research on abductive and default reasoning, probabilistic inference, and relational probabilistic models, and he has recently been working on semantic science, combining ontologies, data, and rich probabilistic theories.