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Frisch, Alan M. Page, Charles David, Jr. 2014-12-17T20:00:46Z 2014-12-17T20:00:46Z 10000-01-01 1993 1993 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). Made available in DSpace on 2014-12-17T20:00:46Z (GMT). No. of bitstreams: 1 9411741.pdf: 9771858 bytes, checksum: 732c272ca669c64bc33aadaa87f4794d (MD5) Previous issue date: 1993 Embargo set by: Seth Robbins for item 72263 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 209 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993. http://hdl.handle.net/2142/72095 (UMI)AAI9411741 Artificial Intelligence Computer Science Anti-Unification in Constraint Logics: Foundations and Applications to Learnability in First-Order Logic, to Speed-Up Learning, and to Deduction text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.