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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Statistical Relational Artificial Intelligence - Logic, Probability, and Computation (Hardcover)
Loot Price: R1,580
Discovery Miles 15 800
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Statistical Relational Artificial Intelligence - Logic, Probability, and Computation (Hardcover)
Series: Synthesis Lectures on Artificial Intelligence and Machine Learning
Expected to ship within 10 - 15 working days
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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.
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