Abstract
We present in this paper a method for finding target hypotheses in Inductive Logic Programming(ILP). In order to find them efficiently, we propose to use abstraction. Given an ILP problem and a hypothesis space H, we first consider an abstraction of H. An abstract space corresponds to a small subspace of H. Then we try to find hypotheses satisfying a certain condition by searching in several such abstract spaces. Since each abstract space is small, the task is not difficult. From these hypotheses, we can easily identify a hypothesis space in which all consistent hypotheses can be found. Since the obtained space is a part of the original H, we can expect that the targets are efficiently found by searching only in the part.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
S. Muggleton (ed.), “Inductive Logic Programming”, Academic Press, 1992.
S. Muggleton and L. De Raedt, “Inductive Logic Programming: Theory and Methods”, Journal of Logic Programming, vol. 12, pp. 629–679, 1994.
E. D. Sacerdoti, “Planning in a Hierarchy of Abstraction Spaces”, Artificial Intelligence, vol. 5, 115–135, 1974.
D. A. Plaisted, “Theorem Proving with Abstraction”, Artificial Intelligence, vol. 16, 47–108, 1981.
J. D. Tenenberg, “Abstraction in Planning”, Reasoning about Plans (James F.Allen et al.), Morgan Kaufmann Publishers, pp. 213–283, 1991.
C. A. Knoblock, “Automatically Generating Abstractions for Planning”, Artificial Intelligence, vol. 68, pp. 243–302, 1994.
F. Giunchiglia and T. Walsh, “A Theory of Abstraction”, Artificial Intelligence, vol. 57, pp. 323–389, 1992.
T. Kakuta, M. Haraguchi and Y. Okubo, “A Goal-Dependent Abstraction for Legal Reasoning by Analogy”, Artificial Intelligence & Law, vol. 5, pp97–118, 1997
Y. Okubo and M. Haraguchi, “Constructing Predicate Mappings for Goal-Dependent Abstraction”, Annals of Mathematics and Artificial Intelligence, vol. 23, pp. 169–197, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Okubo, Y., Haraguchi, M., Zheng, Y.F. (2000). A Method for Finding Consistent Hypotheses Using Abstraction. In: Choueiry, B.Y., Walsh, T. (eds) Abstraction, Reformulation, and Approximation. SARA 2000. Lecture Notes in Computer Science(), vol 1864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44914-0_22
Download citation
DOI: https://doi.org/10.1007/3-540-44914-0_22
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67839-7
Online ISBN: 978-3-540-44914-0
eBook Packages: Springer Book Archive