Téléchargez le livre : Statistical Relational Artificial Intelligence

Statistical Relational Artificial Intelligence

Logic, Probability, and Computation

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Éditeur :

Springer


Collection :

Synthesis Lectures on Artificial Intelligence and Machine Learning

Paru le : 2022-05-31



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Description
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.
Pages
175 pages
Collection
Synthesis Lectures on Artificial Intelligence and Machine Learning
Parution
2022-05-31
Marque
Springer
EAN papier
9783031000225
EAN PDF
9783031015748
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
6932 Ko
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Prix
51,04 €

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