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Nonmonotonic consequence based on intuitionistic logic

Published online by Cambridge University Press:  12 March 2014

Gisèle Fischer Servi*
Affiliation:
Dipartimento di Filosofia, Universitã Delgli Studi di Parma, 43100 Parma (PR), Italy

Extract

Research in AI has recently begun to address the problems of nondeductive reasoning, i.e., the problems that arise when, on the basis of approximate or incomplete evidence, we form well-reasoned but possibly false judgments. Attempts to stimulate such reasoning fall into two main categories: the numerical approach is based on probabilities and the nonnumerical one tries to reconstruct nondeductive reasoning as a special type of deductive process. In this paper, we are concerned with the latter usually known as nonmonotonic deduction, because the set of theorems does not increase monotonically with the set of axioms.

It is generally acknowledged that nonmonotonic (n.m.) formalisms (e.g., [C], [MC1], [MC2] [MD], [MD-D], [Rl], [R2], [S]) are plagued by a number of difficulties. A key issue concerns the fact that most systems do not produce an axiomatizable set of validities. Thus, the chief objective of this paper is to develop an alternative approach in which the set of n.m. inferences, which somehow qualify as being deductively sound, is r.e.

The basic idea here is to reproduce the situation in First Order Logic where the metalogical concept of deduction translates into the logical notion of material implication. Since n.m. deductions are no longer truth preserving, our way to deal with a change in the metaconcept is to extend the standard logic apparatus so that it can reflect the new metaconcept. In other words, the intent is to study a concept of nonmonotonic implication that goes hand in hand with a notion of n.m. deduction. And in our case, it is convenient that the former be characterized within the more tractable context of monotonic logic.

Type
Research Article
Copyright
Copyright © Association for Symbolic Logic 1992

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References

[C]Clark, K. L., Negation as failure, Logic and Data Bases (Gallaire, H. and Minker, J., editors), Plenum, New York, 1978.Google Scholar
[D]Delgrande, J. P., A first order conditional logic for reasoning about prototypical properties, Simon Fraser University, Department of Computing Science, Technical Report, Burnaby, 1986.Google Scholar
[FS]Servi, G. Fischer, Logiche non monotone su base intuizionista, Atti del III convegno nazionale sulla programmazione logica, Roma, 1988.Google Scholar
[F]Fitting, M., Intuitionistic Logic, Model, theory and Forcing, North-Holland, Amsterdam, 1969.Google Scholar
[G1]Gabbay, D., A general filtration method for modal logics, Journal of Philosophical Logic, vol. 1 (1972), pp. 2934.CrossRefGoogle Scholar
[G2]Gabbay, D., Intuitionistic basis for Non Monotonie Logic, Proceedings of the Conference on automated deduction, Lecture Notes in Computer Science, vol. 138, Springer-Verlag, Berlin, 1982, pp. 260273.CrossRefGoogle Scholar
[G3]Gabbay, D., Theoretical foundations for non monotonie reasoning, Logics and Models of concurrent systems (Apt, K. R., editor), Springer-Verlag, Berlin and New York, 1985.Google Scholar
[G4]Gabbay, D., Modal provability foundations for negation by failure 1, Extensions of Logic Programming (Schroeder-Heister, P., editor), Lecture Notes in Computer Science, vol. 475, Springer-Verlag, Berlin, 1991, pp. 179222.CrossRefGoogle Scholar
[L]Lemmon, E. J., An introduction to modal logic, monograph no. 11, Oxford University Press, London and New York, 1977.Google Scholar
[Lw]Lewis, D., Counterfactuals, Harvard University Press, Cambridge, MA, 1973.Google Scholar
[MC1]McCarty, J., Circumscription—a form of non monotonic reasoning, Artificial Intelligence, vol. 13, (1986), pp. 2739.CrossRefGoogle Scholar
[MC2]McCarty, J., Applications of circumscription to formalizing common sense knowledge, Artificial Intelligence, vol. 28 (1986), pp. 89116.CrossRefGoogle Scholar
[MD]McDermott, D., Non Monotonie Logic 2: Non monotonie theories, Journal of the Association for Computing Machinery, vol. 29, (1982), pp. 3357.CrossRefGoogle Scholar
[MD-D]McDermott, D. and Doyle, J., Non monotonie logic 1, Artificial Intelligence, vol. 13, 1980.CrossRefGoogle Scholar
[M]Nute, D., Non monotonic reasoning and conditionals, University of Georgia, Advanced Computational Methods Center, research report 010002, Athens Ga, 1984.Google Scholar
[P]Parikh, R., Logic of knowledge, games and Dynamic logic, FST-TCS, Lecture Notes in Computer Science, vol. 181, Springer-Verlag, Berlin and New York, 1984.Google Scholar
[R1]Reiter, R., On closed world data bases, Logic and Data Bases (Gallaire, H. and Minker, J., editors), Plenum, New York, 1978, pp. 5576.CrossRefGoogle Scholar
[R2]Reiter, R., A logic for default reasoning, Artificial Intelligence, vol. 13 (1980), pp. 81132.CrossRefGoogle Scholar
[R3]Reiter, R., Non monotonic reasoning, Annual Reviews of Computer Science, 1987.Google Scholar
[S]Shoham, Y., Reasoning about change, M. I. T. Press, Cambridge, MA, 1988.Google Scholar
[St]Stalnaker, R., A theory of conditionals, Studies in Logical Theories (Rescher, N., editor), Black-well, Oxford, 1968.Google Scholar