Probabilistic Inductive Logic Programming

356 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Probabilistic Inductive Logic Programming.- Formalisms and Systems.- Relational Sequence Learning.- Learning with Kernels and Logical Representations.- Markov Logic.- New Advances in Logic-Based Probabilistic Modeling by PRISM.- CLP( ): Constraint Logic Programming for Probabilistic Knowledge.- Basic Principles of Learning Bayesian Logic Programs.- The Independent Choice Logic and Beyond.- Applications.- Protein Fold Discovery Using Stochastic Logic Programs.- Probabilistic Logic Learning from Haplotype Data.- Model Revision from Temporal Logic Properties in Computational Systems Biology.- Theory.- A Behavioral Comparison of Some Probabilistic Logic Models.- Model-Theoretic Expressivity Analysis.

• Reihe: Lecture Notes in Computer Science
• Themen: Informatik und Informationstechnologie Informatik Künstliche Intelligenz (KI) Wissensbasierte Systeme, Expertensysteme
• ISBN: 9783540786511
• Sprache: Englisch
• Erscheinungsdatum: 14.03.2008
• Größe: 235 x 155 mm
• Verlag: Springer
• Herausgegeben von: Kristian Kersting, Stephen H. Muggleton, Luc De Raedt, Paolo Frasconi