Abstract
If one desires that an automatic theory formation program detect inconsistency in a set of hypotheses, the Horn clause logic of Prolog is unsuitable as no contradiction is derivable. Full first order logic provides a suitably expressive alternative, but then requires a full first order theorem-prover as the basic theory construction mechanism. Here we present an alternative for augmenting definite clauses with the power to express potentially inconsistent scientific theories. The alternative is based on a partitioning of definite clauses into two categories: ordinary assertions, and integrity constraints. This classification provides the basis for a simple theory formation program. We here describe such a theory formation system based on Prolog, and show how it provides an interesting reformulation of rule-based diagnosis systems like MYCIN.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
K.A Bowen and T. Weinberg (1985), A meta-level extension of Prolog, IEEE 1985 Symposium on Logic Programming, July 15–18, Boston, Massachusetts, 48–53.
J.S. Brown, R.R. Burton, and J. de Kleer (1982), Pedagogical, natural language and knowledge engineering techniques in SOPHIE I, II and III, Intelligent Tutoring Systems, J.S. Brown (eds.), Academic Press, New York, 227–282.
B.G. Buchanan and E.H. Shortliffe (1984, eds.), Rule-Based Expert Systems The MYCIN Experiments of the Stanford Heuristic Programming Project, Addison-Wesley, Reading, Massachusetts.
K.L. Clark (1978), Negation as failure, Logic and Data Bases, H. Gallaire and J. Minker (eds.), Plenum Press, New York, 293–322.
J.J. Finger and M.R. Genesereth (1985), Residue: a deductive approach to design synthesis, STAN-CS-85-1035, Computer Science Department, Stanford University, Stanford, California, January.
M.R. Genesereth (1985), The use of design descriptions in automated diagnosis, Qualitative Reasoning about Physical Systems, D.G. Bobrow (eds.), MIT Press, Cambridge, Massachusetts, 411–436.
R.G. Goebel (1985), DLOG: an experimental PROLOG-based database management system, Proceedings of the IFIP Working Conference on Data Bases in the Humanities and Social Sciences, R.F. Allen (ed.), Paradigm Press, New York, 293–306.
R.G. Goebel (1985), A logic-based data model for the machine representation of knowledge, Ph.D. dissertation, Computer Science Department, The University of British Columbia, Vancouver, British Columbia, October, 253 pages.
P. Hammond (1982), Logic programming for expert systems, DOC 82/4, Department of Computing, Imperial College of Science and Technology, University of London, March.
K.M. Kahn and M. Carlsson (1984), The compilation of Prolog programs without the use of a Prolog compiler, Proceedings of the International Conference on Fifth Generation Computer Systems, November 6–9, Tokyo, Japan, 348–355.
M. Kohli and J. Minker (1983), Intelligent control using integrity constraints, Proceedings of the National Conference on Artificial Intelligence (AAAI-83), August 22–26, University of Maryland/George Washington University, Washinton, D.C., 202–205.
J.W. Lloyd (1984), Foundations of logic programming, Springer-Verlag, New York.
D.W. Loveland (1978), Automated theorem proving: a logical basis, North-Holland, Amsterdam, The Netherlands.
B. Meltzer (1973), The programming of deduction and induction, Artificial and Human Thinking, A. Elithorn and D. Jones (eds.), Jossey-Bass, London, England, 19–33.
T. Miyachi, S. Kunifuji, H. Kitakami, K. Furukawa, A. Takeuchi, and H. Yokota (1984), A knowledge assimiliation method for logic databases, Proceedings of the IEEE International Symposium on Logic Programming, February 6–9, Atlantic City, New Jersey, 118–125.
N.J. Nilsson (1984), Probabilistic logic, Technical Note 321, Artificial Intelligence Center, SRI International, Menlo Park, California, February.
D.L. Poole (1986), Default reasoning and diagnosis as theory formation, Technical Report CS-86-08, Department of Computer Science, University of Waterloo, Waterloo, Ontario, March.
D.L. Poole, R.G. Goebel, and R. Aleliunas (1986), Theorist: a logical reasoning system for defaults and diagnosis, Knowledge Representation, N.J. Cercone and G. McCalla (eds.), Springer-Verlag, New York [invited chapter, submitted September 10, 1985].
H.E. Pople (1977), The formation of composite hypotheses in diagnostic problem solving: an exercise in synthetic reasoning, Proceedings of the Fifth International Joint Conference on Artificial Intelligence, August 22–25, Cambridge, Massachusetts, 1030–1037.
K.R. Popper (1958), The Logic of Scientific Discovery, Harper & Row, New York.
E. Shapiro (1983), Logic programs with uncertainties: a tool for implementing rule-based systems, Proceedings of IJCAI-83, August 8–12, Karlsruhe, Germany, 529–532.
E.Y. Shapiro (1981), An algorithm that infers theories from facts, Proceedings of the Seventh International Joint Conference on Artificial Intelligence, August 24–28, The University of British Columbia, Vancouver, British Columbia, 446–451.
E. Y. Shapiro (1982), Algorithmic program debugging, MIT Press, Cambridge, Massachusetts.
L. Sterling (1984), Logical levels of problem solving, Proceedings of the Second International Logic Programming Conference, July 2–6, Uppsala University, Uppsala, Sweden, 231–242.
A. Takeuchi and Koichi Furukawa (1985), Partial evaluation of Prolog programs and its application to meta programming, Technical report TR-126, Institute for New Generation Computer Technology, Tokyo, Japan, September [to appear in Lecture Notes in Computer Science, Springer].
Z.D. Umrigar and V. Pitchumani (1985), An experiment in programming with full first-order logic, IEEE 1985 Symposium on Logic Programming, July 15–18, Boston, Massachusetts, 40–47.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1986 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Goebel, R., Furukawa, K., Poole, D. (1986). Using definite clauses and integrity constraints as the basis for a theory formation approach to diagnostic reasoning. In: Shapiro, E. (eds) Third International Conference on Logic Programming. ICLP 1986. Lecture Notes in Computer Science, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-16492-8_77
Download citation
DOI: https://doi.org/10.1007/3-540-16492-8_77
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-16492-0
Online ISBN: 978-3-540-39831-8
eBook Packages: Springer Book Archive