A Behavioral Comparison of Some Probabilistic Logic Models

• Published in: Probabilistic Inductive Logic Programming Vol. 4911; pp. 305 - 324
• Main Authors: Muggleton, Stephen, Chen, Jianzhong
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2008; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Artificial intelligence; Bayesian Network; Computer programming / software development; Conditional Probability Table; Descriptive Attribute; Inductive Logic Programming; Logic Program; Mathematical theory of computation

Probabilistic Logic Models (PLMs) are efficient frameworks that combine the expressive power of first-order logic as knowledge representation and the capability to model uncertainty with probabilities. Stochastic Logic Programs (SLPs) and Statistical Relational Models (SRMs), which are considered as...