Journal of Automated Reasoning

, Volume 5, Issue 3, pp 293–307

Weak Generalized Closed World Assumption

  • Arcot Rajasekar
  • Jorge Lobo
  • Jack Minker

DOI: 10.1007/BF00248321

Cite this article as:
Rajasekar, A., Lobo, J. & Minker, J. J Autom Reasoning (1989) 5: 293. doi:10.1007/BF00248321


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 Negation-As-Failure (NF) and the Support-For-Negation (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 Negation-As-Finite-Failure (NAFF), similar to the NF-rule and less cumbersome than the SN-rule. We present three definitions of the NAFF. Two declarative definitions similar to those for the NF-rule and one procedural definition based on SLI-resolution.

Key words

Explicit representation default rules Weak Generalized Closed World Assumption 

Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • Arcot Rajasekar
    • 1
  • Jorge Lobo
    • 1
  • Jack Minker
    • 2
    • 3
  1. 1.Department of Computer ScienceUniversity of MarylandCollege ParkUSA
  2. 2.Department of Computer ScienceUniversity of MarylandCollege ParkUSA
  3. 3.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

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