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Taxonomic Syntax for First-Order Inference

Author(s)
McAllester, David; Givan, Robert
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Abstract
Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.
Date issued
1989-06-01
URI
http://hdl.handle.net/1721.1/6507
Other identifiers
AIM-1134
Series/Report no.
AIM-1134

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  • AI Memos (1959 - 2004)

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