Computing with default logic

  • Paweł Cholewiński
  • , Victor W. Marek
  • , Artur Mikitiuk
  • , Mirosław Truszczyński

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Default logic was proposed by Reiter as a knowledge representation tool. In this paper, we present our work on the Default Reasoning System, DeReS, the first comprehensive and optimized implementation of default logic. While knowledge representation remains the main application area for default logic, as a source of large-scale problems needed for experimentation and as a source of intuitions needed for a systematic methodology of encoding problems as default theories we use here the domain of combinatorial problems. To experimentally study the performance of DeRcS we developed a benchmarking system, the TheoryBase. The TheoryBase is designed to support experimental investigations of nonmonotonic reasoning systems based on the language of default logic or logic programming. It allows the user to create parameterized collections of default theories having similar properties and growing sizes and, consequently, to study the asymptotic performance of nonmonotonic systems under investigation. Each theory generated by the TheoryBase has a unique identifier, which allows for concise descriptions of test cases used in experiments and, thus, facilitates comparative studies. We describe the TheoryBase in this paper and report on our experimental studies of DeReS performance based on test cases generated by the TheoryBase.

Original languageEnglish
Pages (from-to)105-146
Number of pages42
JournalArtificial Intelligence
Volume112
Issue number1
DOIs
StatePublished - Aug 1999

Bibliographical note

Funding Information:
This work was partially supported by the NSF grants IRI-9400568, CDA-9502645 and IRI-9619233.

Funding

This work was partially supported by the NSF grants IRI-9400568, CDA-9502645 and IRI-9619233.

FundersFunder number
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of ChinaIRI-9400568, IRI-9619233, CDA-9502645

    ASJC Scopus subject areas

    • Language and Linguistics
    • Linguistics and Language
    • Artificial Intelligence

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