Abstract
In this paper we argue that the use of a language with a type system, together with higher-order facilities and functions, provides a suitable basis for knowledge representation in inductive concept learning and, in particular, illu minates the relationship between attribute-value learning and inductive logic programming (ILP). Individuals are represented by closed terms: tuples of constants in the case of attribute-value learning; arbitrarily complex terms in the case of ILP. To illustrate the point, we take some learning tasks from the machine learning and ILP literature and represent them in Escher, a typed, higher-order, functional logic programming language being developed at the University of Bristol. We argue that the use of a type system provides better ways to discard meaningless hypotheses on syntactic grounds and encompasses many ad hoc approaches to declarative bias.
Preview
Unable to display preview. Download preview PDF.
References
L. De Raedt & W. Van Laer. Inductive constraint logic. Proc. 6th Int. Workshop on Algorithmic Learning Theory, LNAI 997, pp.80–94, 1995.
L. De Raedt & L. Dehaspe. Clausal Discovery. Machine Learning 26(2/3):99–146, 1997.
J.W. Lloyd. Programming in an Integrated Functional and Logic Language. Journal of Functional and Logic Programming, 1998 (to appear).
T.M. Mitchell. Machine Learning. McGraw-Hill, 1997.
A. Srinivasan, S. Muggleton, R. King & M. Sternberg. Mutagenesis: ILP experiments in a non-determinate biological domain. Proc. 4th Inductive Logic Programming Workshop, GMD-Studien 237, 1994.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Flach, P.A., Giraud-Carrier, C., Lloyd, J.W. (1998). Strongly typed inductive concept learning. In: Page, D. (eds) Inductive Logic Programming. ILP 1998. Lecture Notes in Computer Science, vol 1446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027322
Download citation
DOI: https://doi.org/10.1007/BFb0027322
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64738-6
Online ISBN: 978-3-540-69059-7
eBook Packages: Springer Book Archive