New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
The Appropriateness of Predicate Invention as Bias Shift Operation in ILP
Machine Learning - Special issue on bias evaluation and selection
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Repeat Learning Using Predicate Invention
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Proceedings of the 7th International Conference on Automated Deduction
An integrated framework for the diagnosis and correction of rule-based programs
Theoretical Computer Science
An integrated distance for atoms
FLOPS'10 Proceedings of the 10th international conference on Functional and Logic Programming
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A New IFLP schema is presented as a general framework for the induction of functional logic programs (FLP). Since narrowing (which is the most usual operational semantics of FLP) performs a unification (mgu) followed by a replacement, we introduce two main operators in our IFLP schema: a generalisation and an inverse replacement or intra-replacement, which results in a generic inversion of the transitive property of equality. We prove that this schema is strong complete in the way that, given some evidence, it is possible to induce any program which could have generated that evidence, We outline some possible restrictions in order to improve the tractability of the schema. We also show that inverse narrowing is just a special case of our IFLP schema. Finally, a straightforward extension of the IFLP schema to function invention is illustrated.