Basic Principles of Learning Bayesian Logic Programs

DOI10.1007/978-3-540-78652-8_7zbMath1137.68544OpenAlexW1523817461MaRDI QIDQ5452026

Kristian Kersting, Luc De Raedt

Publication date: 28 March 2008

Published in: Probabilistic Inductive Logic Programming (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/245773

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic programming (68N17)

Related Items (7)

Learning directed probabilistic logical models: Ordering-search versus structure-search ⋮ Approximate classification with web ontologies through evidential terminological trees and forests ⋮ Probabilistic (logic) programming concepts ⋮ Bandit-based Monte-Carlo structure learning of probabilistic logic programs ⋮ Lifted discriminative learning of probabilistic logic programs ⋮ Reference classes and relational learning ⋮ New Advances in Logic-Based Probabilistic Modeling by PRISM

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