swMATH ID: 2784
Software Authors: Laskey, Kathryn Blackmond
Description: A logic system that integrates First Order Logic (FOL) with Bayesian probability theory. MEBN extends ordinary Bayesian networks to allow representation of graphical models with repeated sub-structures. Knowledge is encoded as a collection of Bayesian network fragments (MFrags) that can be instantiated and combined to form highly complex situation-specific Bayesian networks. A MEBN theory (MTheory) implicitly represents a joint probability distribution over possibly unbounded numbers of hypotheses, and uses Bayesian learning to refine a knowledge base as observations accrue. MEBN provides a logical foundation for the emerging collection of highly expressive probability-based languages.
Homepage: http://www.pr-owl.org/mebn/index.php
Keywords: Bayesian network; graphical probability models; knowledge representation; multi-entity Bayesian network; probabilistic logic; uncertainty in artificial intelligence
Related Software: BLOG; PR-OWL; IBAL; PRISM; BayesOWL; BUGS; UnBBayes; SPOOK; KnowRob; MayBMS; NUTS; Dsharp; Figaro; FACTORIE; Church; CP-logic; ProbLog; z3; Yices; Graphplan
Referenced in: 11 Publications

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