Bitte benutzen Sie diese Referenz, um auf diese Ressource zu verweisen: doi:10.22028/D291-40267
Titel: Compartmentalized Connection Graphs for Concurrent Logic Programming I : Compartmentalization, Transformation and Examples
VerfasserIn: Powers, David M. W.
Sprache: Englisch
Erscheinungsjahr: 1990
Erscheinungsort: Kaiserslautern
DDC-Sachgruppe: 004 Informatik
Dokumenttyp: Forschungsbericht (Report zu Forschungsprojekten)
Abstract: The research reported in this paper and its sequels represents a revolt against the explicit and restricitve control of PROLOG and the present generation of Concurrent and Parallel Logic Programming Languages. It returns to the original Connection Graph paradigm of Kowalski and provides a methodology for logic programming in this framework. An elementary analysis of where the expenses in executing a logic program occur shows how processing of each of the linear components in a proof (or execution trace) can be executed in (non-deterministic) logarithmic time within the CONG system. Our implementation demonstrates that lemmatization can result in even more dramatic improvement. This paper deals primarily with recursion both in relation to connection graphs and in relation to Horn logic programs. In the first case a modified “compartmentalized” connection graph framework emerges, which allows proofs which are in general logarithmic in the size of a conventional connection graph proof. Furthermore, in the latter case we exhibit a technique allowing arbitrary recursive predicates in a logic program to be reduced to a canonical form involve only one single recursive predicate. The method is demonstrated on standard PROLOG examples.
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-402673
hdl:20.500.11880/36222
http://dx.doi.org/10.22028/D291-40267
Schriftenreihe: SEKI-Report / Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI [ISSN 1437-4447]
Band: 90,16
Datum des Eintrags: 11-Aug-2023
Fakultät: SE - Sonstige Einrichtungen
Fachrichtung: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Professur: SE - Sonstige
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes



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