Please use this identifier to cite or link to this item: doi:10.22028/D291-25225
Title: A consequence-finding approach for feature recognition in CAPP
Author(s): Hinkelmann, Knut
Language: English
Year of Publication: 1994
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1994
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: We present a rewriting approach for a consequence-finding inference of logic programs. Consequence finding restricts the derivations of a logic program to exactly those facts that depend on an explicitly given set of initial facts. The rewriting approach extends the Generalized Magic Sets rewriting, well-known from deductive databases, by an up propagation in addition to the usual down propagation. The initial motivation for this inference was to realize the abstraction phase of a knowledge-based CAPP system for lathe turning. The input to the CAPP system is a detailed description of a workpiece. During the abstraction phase characteristic parts, called features, are recognized for which predefined skeletal plans exist. Consequence finding is a method to restrict the computation such that exactly the features of the actual workpiece are derived. The same inference can also be used for checking integrity constraints: given an update of a deductive database or a logic program, consequence finding applies only those rules that are effected by the update operation.
Link to this record: urn:nbn:de:bsz:291-scidok-50425
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 94-11
Date of registration: 7-Feb-2013
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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