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Report (Bericht) zugänglich unter
An alternative proof method for possibilistic logic and its application to terminological logics
URN: urn:nbn:de:bsz:291-scidok-37984
URL: http://scidok.sulb.uni-saarland.de/volltexte/2011/3798/
Quelle:
(1993) Kaiserslautern ; Saarbrücken : DFKI, 1993
pdf-Format:
Dokument 1.pdf (13.095 KB)
SWD-Schlagwörter:
Künstliche Intelligenz
Institut:
DDC-Sachgruppe:
Informatik
Dokumentart:
Report (Bericht)
Schriftenreihe:
Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Bandnummer:
93-01
Sprache:
Englisch
Erstellungsjahr:
1993
Publikationsdatum:
05.07.2011
Kurzfassung auf Englisch:
Possibilistic logic, an extension of first-order logic, deals with uncertainty that can be estimated in terms of possibility and necessity measures. Syntactically, this means that a first-order formula is equipped with a possibility degree or a necessity degree that expresses to what extent the formula is possibly or necessarily true. Possibilistic resolution, an extension of the well-known resolution principle, yields a calculus for possibilistic logic which respects the semantics developed for possibilistic logic. A drawback, which possibilistic resolution inherits from classical resolution, is that it may not terminate if applied to formulas belonging to decidable fragments of first-order logic. Therefore we propose an alternative proof method for possibilistic logic. The main feature of this method is that it completely abstracts from a concrete calculus but uses as basic operation a test for classical entailment. If this test is decidable for some fragment of first-order logic then possibilistic reasoning is also decidable for this fragment. We then instantiate possibilistic logic with a terminological logic, which is a decidable subclass of first-order logic but nevertheless much more expressive than propositional logic. This yields an extension of terminological logics towards the representation of uncertain knowledge which is satisfactory from a semantic as well as algorithmic point of view.
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