Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Generalized teaching dimensions and the query complexity of learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
How many queries are needed to learn?
Journal of the ACM (JACM)
Learning horn definitions: theory and an application to planning
New Generation Computing - Special issue on inductive logic programming 97
Learning Function-Free Horn Expressions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Algorithmic Program DeBugging
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Learning Horn Expressions with LogAn-H
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning Acyclic First-Order Horn Sentences from Entailment
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Learning First-Order Acyclic Horn Programs from Entailment
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Anti-unification in constraint logics: Foundations and applications to learnability in first-order logic, to speed-up learning, and to deduction
Pac-learning recursive logic programs: efficient algorithms
Journal of Artificial Intelligence Research
Pac-learning recursive logic programs: negative results
Journal of Artificial Intelligence Research
Polynomial certificates for propositional classes
Information and Computation
Complexity parameters for first order classes
Machine Learning
Learning Horn Expressions with LOGAN-H
The Journal of Machine Learning Research
Polynomial certificates for propositional classes
Information and Computation
The subsumption lattice and query learning
Journal of Computer and System Sciences
Learning hereditary and reductive prolog programs from entailment
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Learning conditional preference networks
Artificial Intelligence
Inductive logic programming: yet another application of logic
INAP'05 Proceedings of the 16th international conference on Applications of Declarative Programming and Knowledge Management
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The paper studies the learnability of Horn expressions within the framework of learning from entailment , where the goal is to exactly identify some pre-fixed and unknown expression by making queries to membership and equivalence oracles. It is shown that a class that includes both range restricted Horn expressions (where terms in the conclusion also appear in the condition of a Horn clause) and constrained Horn expressions (where terms in the condition also appear in the conclusion of a Horn clause) is learnable. This extends previous results by showing that a larger class is learnable with better complexity bounds. A further improvement in the number of queries is obtained when considering the class of Horn expressions with inequalities on all syntactically distinct terms.