An Integrated Non-Monotonic Deduction and Reason Maintenance System

  • Michael Reinfrank
  • Hartmut Freitag
Conference paper
Part of the Informatik-Fachberichte book series (volume 162)


KAPRI⋆⋆ uses rules of the form ifunlessthen … . For such a rule to be fired, its monotonie if-antecedents are required to match the current database, while none of its non-monotonic unless-antecedents does. The current state of a KAPRI-system is represented by a dependency network composed of assertions and corresponding justifications for believing in them in terms of belief respectively disbelief in other assertions. This network is maintained by a reason maintenance system, KL-DNMS⋆⋆, that revises the current belief status with respect to every modification due to the firing of a rule or to the addition/retraction of a basic fact.


Belief Revision Ground Instance Dependency Network Monotonic Rule Admissible Extension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [AI-13-80]
    Bobrow, Daniel (edt.): Special Issue on Non-Monotonic Reasoning. ARTIFICIAL INTELLIGENCE 13 (1,2) (1980)Google Scholar
  2. [Charniak|Sussman|Winograd-71]
    Charniak, Eugene; Sussman, Gerald; Winograd, Terry: MICRO-PLANNER Reference Manual. Memo 203A, MIT Al-Lab (Cambridge, December 1971 )Google Scholar
  3. [deKleer-84]
    deKleer, Johan: Choices without Backtracking. Proc. 4th NCAI, pp. 79–85 (Austin, 1984 )Google Scholar
  4. [deKleer-85a]
    deKleer, Johan: An Assumption-Based TMS. Research Report Draft, Xerox Pare (September, 1985 )Google Scholar
  5. [deKleer-85b]
    deKleer, Johan: Personal communication. (GWAI 85, Dassel, September 1985 )Google Scholar
  6. [deKleer|Doyle|Steele|Sussman-79]
    deKleer, Johan; Doyle, Jon; Steele, Guy; Sussman; Gerald: Explicit Control of Reasoning. In Winston; Brown (eds.): ARTIFICIAL INTELLIGENCE - AN MIT PERSPECTIVE, MIT Press (Cambridge, 1979 )Google Scholar
  7. [Doyle-79]
    Doyle, Jon: A Truth Maintenance System. Al 12, pp. 231–272 (1979)MathSciNetGoogle Scholar
  8. [Doyle-83]
    Doyle, Jon: Some Theories of Reasoned Assumptions. CMU-CS-83-125, CMU (Pittsburgh, May 1983 )Google Scholar
  9. [Doyle|McDermott-80]
    Doyle, Jon; McDermott, Drew: Non-Monotonic Logic I. Al 13 (1,2), pp. 41–72 (April 1980)MathSciNetMATHGoogle Scholar
  10. [Fikes|Nilsson-71]
    Fikes, Richard E.; Nilsson, N.J.: STRIPS - A New Approach to the Application of Theorem Proving to Problem Solving. Al 2 (3,4), pp.189–208(1971)Google Scholar
  11. [Forgy-81]
    Forgy, Charles L.: The OPS5 user’s manual. CMU-CDS-81-135, CMU (Pittsburgh, 1981 )Google Scholar
  12. [Forgy-82]
    Forgy, Charles L.: RETE: A Fast Algorithm for the Many Pattern/Many Object Match Problem. Artificial Intelligence 19, pp.17–38(1982)Google Scholar
  13. [Freitag|Klug|Reinfrank-85]
    Freitag, Hartmut; Klug, Juergen; Reinfrank, Michael:KL-DNMS, ein System zur Verwaltung nicht-monotoner Abhaengigkeitsnetze. Interner Bericht, FB Informatik, Univ. Kaiserslautern (Kaiserslautern, 1985 )Google Scholar
  14. [Goldstein|Roberts-77]
    Goldstein, Ira; Roberts, B.R.: The FRL Manual. TR 409, MIT AI-Lab, ( Cambridge, 1977 )Google Scholar
  15. [Goodwin-82]
    Goodwin, James: An Improved Algorithm for Non-Monotonic Dependency Net Update. LITH-MAT-R-82-23, Linkoeping University ( Linkoeping, August 1982 )Google Scholar
  16. [Goodwin-84]
    Goodwin, James: WATSON: A Dependency Directed Inference System. Proc. WS-NMR, pp. 103–114 ( New Paltz, October 1984 )Google Scholar
  17. [Hayes-71]
    Hayes, Patrick: The Frame Problem, and Related Problems on Artificial Intelligence. Memo AIM-153, Stanford Artificial Intelligence Project ( Stanford, November 1971 )Google Scholar
  18. [Hayes-Roth-85]
    Hayes-Roth, Frederick: Rule-Based Systems. CACM 28 (9), pp. 921–932, (September 1985)Google Scholar
  19. [KEE-84]
    The Knowledge Engineering Environment. Intellicorp, Menlo Park, CA (1984)Google Scholar
  20. [Moore-83]
    Moore, Robert C.: Semantical Considerations on Non-Monotonic Logic. TechNote 284, SRI (Menlo Park, 1983 )Google Scholar
  21. [Moore-84]
    Moore, Robert C.: Possible World Semantics for Autoepistemic Logic. Proc. WS-NMR, pp. 344-354 ( New Paltz, October 1984 )Google Scholar
  22. [Minsky-74]
    Minsky, Marvin: A Framework for Representing Knowledge. Memo 306, MIT Al-Lab (Cambridge, June 1974 )Google Scholar
  23. [Orejel-Opisso-84]
    Orejel-Opisso, Jorge L.: Story Understanding with WATSON, a Computer Program Modelling Natural Language Inferences Using Non-Monotonic Dependencies. Report T-146, Univ. of Illinois at Urbana-Champaign (Urbana, May 1984 )Google Scholar
  24. [Reinfrank-85]
    Reinfrank, Michael: An Introduction to Non-Monotonic Reasoning. MEMO SEKI-85-02, Univ. Kaiserslautern (Kaiserslautern, 1985 )Google Scholar
  25. [Reinfrank-87]
    Reinfrank, Michael: Admissible Extension Formalisms for a Rule-Based Non-Monotonic Inference System. Technical Report, Linkoeping University, in preparation.Google Scholar
  26. [Reinfrank et al -86]
    Reinfrank, Michael; Beetz, Michael; Freitag, Hartmut; Klug, Juergen: KAPRI - A Rule-Based Non-Monotonic Inference Engine with an Integrated Reason Maintenance System. SEKI-REPORT SR-86-03, Univ. Kaiserslautern (Kaiserslautern, March 1986 )Google Scholar
  27. [Reiter-80]
    Reiter, Raymond: A Logic for Default Reasoning. Al 13 (1,2), pp. 81–132, (April 1980)MathSciNetMATHGoogle Scholar
  28. [Sandewall-72]
    Sandewall, Erik: An Approach to the Frame Problem, and its Implementation. In Meitzer, B.; Michie, D. (eds.) MACHINE INTELLIGENCE 7, pp. 195-204(1972)Google Scholar
  29. [Sandewall-85]
    Sandewall, Erik: A Functional Approach to Non-Monotonic Logic. Proc. 9th IJCAI 85, pp. 100 - 106 (1985)Google Scholar
  30. [Stallman|Sussman-77]
    Stallman, Richard; Sussman, Gerald: Forward Reasoning and Dependency-Directed Backtracking in a System for Computer-Aided Circuit Analysis. Artificial Intelligence 9, pp. 135 - 196 (1977)MATHCrossRefGoogle Scholar
  31. [Williams-84]
    Williams, Chuck: ART, The Advanced Reasoning Tool: Conceptual Overview. Inference Corporation (Los Angeles, 1984 )Google Scholar
  32. [Winston-82]
    Winston, Patrick H.: Learning by Augmenting Rules and Accumulating Censors. Memo 678, MIT Al-Lab (Cambridge, May 1982, revised February 1984 )Google Scholar
  33. [Winograd-80]
    Winograd, Terry: Extended Inference Modes in Reasoning by Computer Systems. Al 13 (1,2), pp. 5–26 (April 1980)MathSciNetMATHGoogle Scholar
  34. [WSNMR-84]
    Proceedings of the Workshop on Non-Monotonic Reasoning (New Paltz, October 1984)Google Scholar
  35. [YES/MVS-Group-84]
    Ennis, H.L.; Griesmer, J.H.; Hong, S.J.; Karnaugh, M.; Kastner, J.K.; Klein, D.A.; Millikn, K.R.; Schor, M.I.; vanWoerkem, H.M.: YES/MVS: A Continous Real Time Expert System. Proc. 4th NCAI, pp. 130–136 (Austin, 1984 )Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Michael Reinfrank
    • 1
  • Hartmut Freitag
    • 2
  1. 1.Dept. of Computer and Information Science RKLLABLinkoeping UniversityLinkoepingSweden
  2. 2.ZT ZTI INF 312Siemens AGMuenchen 83Germany

Personalised recommendations