Horn approximations of empirical data

DOI10.1016/0004-3702(94)00072-9zbMath1014.03514OpenAlexW1971132311MaRDI QIDQ1855210

Michael Kearns, Bart Selman, Henry A. Kautz

Publication date: 4 February 2003

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0004-3702(94)00072-9

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Logic in computer science (03B70) Mechanization of proofs and logical operations (03B35)

Related Items (28)

Reasoning with ordered binary decision diagrams ⋮ What makes propositional abduction tractable ⋮ Horn axiomatizations for sequential data ⋮ From equivalence queries to PAC learning: the case of implication theories ⋮ Defaults and relevance in model-based reasoning ⋮ On the Boolean connectivity problem for Horn relations ⋮ On the hardness of approximate reasoning ⋮ Mining ℰℒ⊥ Bases with Adaptable Role Depth ⋮ The inverse satisfiability problem ⋮ Matroid Horn functions ⋮ Bidual Horn functions and extensions ⋮ First order LUB approximations: characterization and algorithms ⋮ Approximate inference of functional dependencies from relations ⋮ The joy of implications, aka pure Horn formulas: mainly a survey ⋮ Parameterized ceteris paribus preferences over atomic conjunctions under conservative semantics ⋮ Optimizations in computing the Duquenne-Guigues basis of implications ⋮ On the difference of Horn theories ⋮ Symbolic knowledge extraction from trained neural networks: A sound approach ⋮ On the Merge of Factor Canonical Bases ⋮ Probably approximately correct learning of Horn envelopes from queries ⋮ Translation among CNFs, characteristic models and ordered binary decision diagrams ⋮ Horn representation of a concept lattice ⋮ Double Horn functions ⋮ Semantical and computational aspects of Horn approximations ⋮ Ordered binary decision diagrams as knowledge-bases ⋮ The complexity of theory revision ⋮ On functional dependencies in \(q\)-Horn theories ⋮ Approximate computation of exact association rules

Cites Work

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• Structure identification in relational data
• Learning conjunctions of Horn clauses
• Support set selection for abductive and default reasoning
• Linear-time algorithms for testing the satisfiability of propositional horn formulae
• On the Structure of Armstrong Relations for Functional Dependencies
• Knowledge compilation and theory approximation
• On sentences which are true of direct unions of algebras
• The decision problem for some classes of sentences without quantifiers

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