A first-order logic for reasoning under uncertainty using rough sets

Simon Parsons, Miroslav Kubat

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

Reasoning with uncertain information is a problem of key importance when dealing with knowledge from real situations. Obtaining the precise numbers required by many uncertainty-handling formalisms can be a problem when building real systems. The theory of rough sets allows us to handle uncertainty without the need for precise numbers, and so has some advantages in such situations. The authors develop a set of symbolic truth values based upon rough sets which may be used to augment predicate logic, and provide methods for combining these truth values so that they may be propagated when augmented logic formulae are used in automated reasoning.

Original languageEnglish (US)
Pages (from-to)211-223
Number of pages13
JournalJournal of Intelligent Manufacturing
Volume5
Issue number4
DOIs
StatePublished - Aug 1 1994
Externally publishedYes

Keywords

  • possible worlds
  • principle
  • resolution
  • rough sets
  • rules of inference
  • theorem proving
  • Uncertainty

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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