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Logic programming

Published: 01 September 1985 Publication History

Abstract

Logic programming is programming by description. The programmer describes the application area and lets the program choose specific operations. Logic programs are easier to create and enable machines to explain their results and actions.

References

[1]
Clocksin. W.F. and Mellish. C.S. Programming in PROLOG. Springer- Verlag. New York. 1981.
[2]
Genesereth, M.R. Partial programs. HPP-84-l. Heuristic Programming Project. Stanford University. Calif., 1984.
[3]
Genesereth, M.R. The role of design descriptions in automated diagnosis. Artif. Infell. 24, 1-3 (Dec. 1984). 411-436.
[4]
Genesereth. M.R. Greiner. R. and Smith, D.E. MRS-A meta-level representation system. HPP-83-27. Heuristic Programming Project. Stanford University, Calif. 1983.
[5]
Hayes, P. Computation and deduction. In Proceedings of fhe 2nd MFCS Symposium. Czechoslovak Academy of Sciences, 1973, pp. 105-118.
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Kowalski. R. Algorithm = logic + control. Commun. ACM 22. 7 (July 1979). 424-436.
[7]
Kowalski. R. Logic for Problem Solving. North-Holland. Amsterdam. 1979.
[8]
McCarthy, J. Programs with common sense. In Semanfic lnformafion Processing, M. Minsky. Ed. MIT Press. Cambridge. Mass. 1968, pp. 403-410.
[9]
Moran, T. Efficient PROLOG pushes AI into wider market. Mini- Micro Sysf. (Feb. 1985).
[10]
Smith, D.E., and Genesereth. M.R. Ordering conjunctive queries. Arfif. Infell. 26, 2 {May 1985). 171-215.

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Ralph Walter Wilkerson

This paper presents a brief, yet very informative and readable, introduction to logic programming and its relationship to PROLOG as a software methodology. Both the advantages and disadvantages of using this methodology are presented. In particular, the limitations of logic programming as regards to its deductive methods and user control are discussed. All in all, this is a good paper for those interested in a quick overview of the subject.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 1985
Published in CACM Volume 28, Issue 9

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  • (2020)Introduction to Logic ProgrammingSynthesis Lectures on Artificial Intelligence and Machine Learning10.2200/S00966ED1V01Y201911AIM04414:1(1-219)Online publication date: 10-Feb-2020
  • (2014)PROLOG for COBOL ProgrammersJournal of Research on Computing in Education10.1080/08886504.1989.1078188321:3(326-338)Online publication date: 25-Feb-2014
  • (2014)An Expert System Construction Approach to CAI DevelopmentJournal of Research on Computing in Education10.1080/08886504.1988.1078186621:2(129-140)Online publication date: 25-Feb-2014
  • (2010)Enhancing Inference in Relational Reinforcement Learning Via Truth Maintenance SystemsProceedings of the 2010 Ninth International Conference on Machine Learning and Applications10.1109/ICMLA.2010.67(407-413)Online publication date: 12-Dec-2010
  • (2010)A framework for computer aided investigation of crime in developing countriesInformation Technology for Development10.1080/02681102.1988.96271183:2(101-109)Online publication date: 12-Jul-2010
  • (2005)MonitorMining: creating domain knowledge for system automation using a gray-box approach2005 9th IFIP/IEEE International Symposium on Integrated Network Management, 2005. IM 2005.10.1109/INM.2005.1440771(61-74)Online publication date: 2005
  • (2005)Une introduction à Prolog IIIFoundations of Data Organization and Algorithms10.1007/3-540-51295-0_137(263-288)Online publication date: 31-May-2005
  • (2005)An application of abstract interpretation in source level program transformationProgramming Languages Implementation and Logic Programming10.1007/3-540-50820-1_39(35-57)Online publication date: 29-May-2005
  • (2005)Guiding inference through relational reinforcement learningProceedings of the 15th international conference on Inductive Logic Programming10.1007/11536314_2(20-37)Online publication date: 10-Aug-2005
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