Please use this identifier to cite or link to this item: doi:10.22028/D291-24967
Title: Deduction-based refinement planning
Author(s): Stephan, Werner
Biundo, Susanne
Language: English
Year of Publication: 1995
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1995
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: We introduce a method of deduction-based refinement planning where prefabricated general solutions are adapted to special problems. Refinement proceeds by stepwise transforming non-constructive problem specifications into executable plans. For each refinement step there is a correctness proof guaranteeing the soundness of refinement and with that the generation of provably correct plans. By solving the hard deduction problems once and for all on the abstract level, planning on the concrete level becomes more efficient. With that, our approach aims at making deductive planning feasible in realistic contexts. Our approach is based on a temporal logic framework that allows for the representation of specifications and plans on the same linguistic level. Basic actions and plans are specified using a programming language the constructs of which are formulae of the logic. Abstract solutions are represented as - possibly recursive - procedures. It is this common level of representation and the fluid transition between specifications and plans our refinement process basically relies upon.
Link to this record: urn:nbn:de:bsz:291-scidok-37560
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 95-13
Date of registration: 30-Jun-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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