Communications of the ACM
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
Learnability by fixed distributions
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Editorial: Advice to Machine Learning Authors
Machine Learning
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Learning nonrecursive definitions of relations with LINUS
EWSL-91 Proceedings of the European working session on learning on Machine learning
Learning simple concepts under simple distributions
SIAM Journal on Computing
Interactive Concept-Learning and Constructive Induction by Analogy
Machine Learning
Algorithmic Program DeBugging
Knowledge Acquisition from Structured Data: Using Determinate Literals to Assist Search
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Bayesian inductive logic programming
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Inductive logic programming: derivations, successes and shortcomings
ACM SIGART Bulletin
Inductive logic programming and learnability
ACM SIGART Bulletin
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Learning logic programs by using the product homomorphism method
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Learning first order universal Horn expressions
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Learning atomic formulas with prescribed properties
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Hardness Results for Learning First-Order Representations and Programming by Demonstration
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Machine Learning
Learning Function-Free Horn Expressions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
An extended transformation approach to inductive logic programming
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Polynomial-time learnability of logic programs with local variables from entailment
Theoretical Computer Science - Algorithmic learning theory
An introduction to inductive logic programming
Relational Data Mining
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
Phase Transitions in Relational Learning
Machine Learning
Mind change complexity of learning logic programs
Theoretical Computer Science
Mind Change Complexity of Learning Logic Programs
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
Learning from Entailment of Logic Programs with Local Variables
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Scalability Issues in Inductive Logic Programming
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
LIME: A System for Learning Relations
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
On the Hardness of Learning Acyclic Conjunctive Queries
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
On Sufficient Conditions for Learnability of Logic Programs from Positive Data
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Complexity in the case against accuracy estimation
Theoretical Computer Science
Relational learning as search in a critical region
The Journal of Machine Learning Research
Metaqueries: semantics, complexity, and efficient algorithms
Artificial Intelligence
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Complexity parameters for first order classes
Machine Learning
Prediction-hardness of acyclic conjunctive queries
Theoretical Computer Science - Algorithmic learning theory (ALT 2000)
Feature Construction Using Theory-Guided Sampling and Randomised Search
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Induction of first-order decision lists: results on learning the past tense of English verbs
Journal of Artificial Intelligence Research
Pac-learning recursive logic programs: efficient algorithms
Journal of Artificial Intelligence Research
Pac-learning recursive logic programs: negative results
Journal of Artificial Intelligence Research
Towards efficient metaquerying
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Relational learning for NLP using linear threshold elements
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
The complexity of theory revision
Artificial Intelligence
Modalities, Relations, and Learning
RelMiCS '09/AKA '09 Proceedings of the 11th International Conference on Relational Methods in Computer Science and 6th International Conference on Applications of Kleene Algebra: Relations and Kleene Algebra in Computer Science
Learning with feature description logics
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Cryptographic limitations on learning one-clause logic programs
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Pac-learning a restricted class of recursive logic programs
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Learnability in inductive logic programming: some basic results and techniques
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Learning trees and rules with set-valued features
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Learnability of simply-moded logic programs from entailment
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
On generalization and subsumption for ordered clauses
JSAI'05 Proceedings of the 2005 international conference on New Frontiers in Artificial Intelligence
Generalization behaviour of alkemic decision trees
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
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The field of Inductive Logic Programming (ILP) is concerned with inducing logic programs from examples in the presence of background knowledge. This paper defines the ILP problem, and describes the various syntactic restrictions that are commonly used for learning first-order representations. We then derive some positive results concerning the learnability of these restricted classes of logic programs, by reduction to a standard propositional learning problem. More specifically, k-clause predicate definitions consisting of determinate, function-free, non-recursve Horn clauses with variables of bounded depth are polynomially learnable under simple distributions. Similarly, recursive k-clause definitions are polynomially learnable under simple distributions if we allow existential and membership queries about the target concept.