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Title:Anti-Unification in Constraint Logics: Foundations and Applications to Learnability in First-Order Logic, to Speed-Up Learning, and to Deduction
Author(s):Page, Charles David, Jr
Doctoral Committee Chair(s):Frisch, Alan M.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Artificial Intelligence
Computer Science
Abstract:Unification is central to automated reasoning. Unification comes in a variety of forms, all of which compute (roughly stated) the greatest lower bound, or all maximal lower bounds, of any two or more syntactic objects in a partially-ordered set of such objects. The dual of unification is an operation called generalization, or anti-unification, which computes least or minimal upper bounds. As with unification, anti-unification comes in a variety of forms. The thesis of this dissertation is: anti-unification in its various forms is, like unification, a powerful tool for automated reasoning. In defense of the thesis, several forms of anti-unification in constraint logic, anti-unification relative to background information, are defined, and their semantic and computational properties are studied. It is shown that these forms of anti-unification are applicable to inductive logic programming (inductive learning of logic programs), speed-up learning, and knowledge base vivification (an approach to efficient deduction).
Issue Date:1993
Description:209 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993.
Other Identifier(s):(UMI)AAI9411741
Date Available in IDEALS:2014-12-17
Date Deposited:1993

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