Weak Generalized Closed World Assumption
 Arcot Rajasekar,
 Jorge Lobo,
 Jack Minker
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Explicit representation of negative information in logic programs is not feasible in many applications such as deductive databases and artificial intelligence. Defining default rules which allow implicit inference of negated facts from positive information encoded in a logic program has been an attractive alternative to the explicit representation approach. There is, however, a difficulty associated with implicit default rules. Default rules such as the CWA and the GCWA, which closely model logical negation, are in general computationally intractable. This has led to the development of weaker definitions of negation such as the NegationAsFailure (NF) and the SupportForNegation (SN) rules which are computationally simpler. These are sound implementations of the CWA and the GCWA, respectively. In this paper, we define an alternative rule of negation based upon the fixpoint definition of the GCWA. This rule, called the Weak Generalized Closed World Assumption (WGCWA), is a weaker definition of the GCWA that allows us to implement a sound negation rule, called the NegationAsFiniteFailure (NAFF), similar to the NFrule and less cumbersome than the SNrule. We present three definitions of the NAFF. Two declarative definitions similar to those for the NFrule and one procedural definition based on SLIresolution.
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 Title
 Weak Generalized Closed World Assumption
 Journal

Journal of Automated Reasoning
Volume 5, Issue 3 , pp 293307
 Cover Date
 19890901
 DOI
 10.1007/BF00248321
 Print ISSN
 01687433
 Online ISSN
 15730670
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 Explicit representation
 default rules
 Weak Generalized Closed World Assumption
 Industry Sectors
 Authors

 Arcot Rajasekar ^{(1)}
 Jorge Lobo ^{(1)}
 Jack Minker ^{(2)} ^{(3)}
 Author Affiliations

 1. Department of Computer Science, University of Maryland, 20742, College Park, MD, USA
 2. Department of Computer Science, University of Maryland, 20742, College Park, MD, USA
 3. Institute for Advanced Computer Studies, University of Maryland, 20742, College Park, MD, USA