John M. Zelle, Raymond J. Mooney, and Joshua B. Konvisser
This paper describes a new method for inducing logic programs from examples which attempts to integrate the best aspects of existing ILP methods into a single coherent framework. In particular, it combines a bottom-up method similar to GOLEM with a top-down method similar to FOIL. It also includes a method for predicate invention similar to CHAMP and an elegant solution to the ``noisy oracle'' problem which allows the system to learn recursive programs without requiring a complete set of positive examples. Systematic experimental comparisons to both GOLEM and FOIL on a range of problems are used to clearly demonstrate the advantages of the approach.
In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), pp. 343--351, Rutgers, NJ, July 1994.

Raymond J. Mooney Faculty mooney [at] cs utexas edu
John M. Zelle Ph.D. Alumni john zelle [at] wartburg edu