Abstract
The present paper discusses a generalization operator based on the λ-subsumption ordering between Horn clauses introduced by the author elsewhere. It has been shown that λ-subsumption is strictly stronger than θ-subsumption and a local equivalent of generalized subsumption. With some language restrictions it is decidable and possesses some other useful properties. Most importantly it allows defining a non-trivial upper bound of the λ-subsumption generalization hierarchy without the use of negative examples. Consequently this allows solving a version of the ILP task with positive-only examples.
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References
Bergadano, F., Gunetti, D. Functional Inductive Logic Programming with Queries to the User, in: Proceedings of ECML-93, LNAI, Vol.667, Springer-Verlag, 1993, 323–328.
Buntine, W. Generalized Subsumption and Its Application to Induction and Redundancy, Artificial Intelligence, Vol. 36 (1988), 149–176.
Conklin, D., Witten, I. Complexity-Based Induction, Machine Learning, Vol. 16(3), 1994, 203–225.
Markov, Z. λ-Subsumption and Its Application to Learning from Positive-only Examples, in: Muggleton (ed.), Proceedings of ILP-96, Selected Papers, Lecture Notes in Artificial Intelligence, Vol.1314, Springer, 1997, 377–396.
Muggleton, S. Inverse Entailment and Progol, New Generation Computing, 13 (1995), 245–286.
Muggleton, S. Learning from positive data, in: Proceedings of ILP-96, Department of Computer and Systems Science, Stockholm University/Royal Institute of Technology, Report No.96-019, August, 1996, 225–244.
Muggleton, S. Stochastic Logic Programs, in: L.De Raedt (ed.), Advances in In-ductive Logic Programming, IOS Press, 1996, 254–264.
Quinlan, J.R. Learning logical definitions from relations, Machine Learning, 5 (1990), 239–266.
Quinlan, J.R. Learning First-Order Definitions of Functions, Journal of Artificial Intelligence Research, 5 (1996), 139–161.
Shapiro, E.Y. Algorithmic program debugging, MIT Press, 1983.
Stahl, L, Tausend, B., Wirth, R. Two Methods for Improving Inductive Logic Pro-gramming Systems, in: Proceedings of ECML-93, LNAI, Vol.667, Springer-Verlag, 1993,41–55.
Van der Laag, P.R.J. An Analysis of Refinement operators in Inductive Logic Programming, Ph.D. thesis, Tinbergen Institute Research Series, No.102, Amsterdam, 1996.
Zelle, J., Thompson, C., Califf, M., Mooney, R. Inducing Logic Programs without Explicit Negative Examples, in: Luc De Raedt (Ed.), Proceedings of ILP-95, Scientific report, Department of Computer Science, K.U. Leuven, September, 1995, 403–416. *** DIRECT SUPPORT *** A0008D21 00007
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© 1998 Springer-Verlag Berlin Heidelberg
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Markov, Z. (1998). Generalization under implication by λ-subsumption. In: Page, D. (eds) Inductive Logic Programming. ILP 1998. Lecture Notes in Computer Science, vol 1446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027325
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DOI: https://doi.org/10.1007/BFb0027325
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