Communications of the ACM
Information Processing Letters
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Generalized subsumption and its applications to induction and redundancy
Artificial Intelligence
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
Implication of clauses is undecidable
Theoretical Computer Science
Prediction-preserving reducibility
Journal of Computer and System Sciences - 3rd Annual Conference on Structure in Complexity Theory, June 14–17, 1988
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
Computational learning theory: an introduction
Computational learning theory: an introduction
PAC-learnability of determinate logic programs
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Belief updating from integrity constraints and queries
Artificial Intelligence
Satisfiability of the smallest binary program
Information Processing Letters
Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Algorithmic Program DeBugging
Knowledge Acquisition and Machine Learning
Knowledge Acquisition and Machine Learning
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Knowledge Acquisition from Structured Data: Using Determinate Literals to Assist Search
IEEE Expert: Intelligent Systems and Their Applications
Learning Logical Definitions from Relations
Machine Learning
Learning Conjunctive Concepts in Structural Domains
Machine Learning
Generalization under Implication by using Or-Introduction
ECML '93 Proceedings of the European Conference on Machine Learning
Too Much Can be Too Much for Learning Efficiently
AII '92 Proceedings of the International Workshop on Analogical and Inductive Inference
Higher-order Concepts in a Tractable Knowledge Representation
GWAI '87 Proceedings of the 11th German Workshop on Artificial Intelligence
A Multistrategy Approach to Relational Knowledge Discovery inDatabases
Machine Learning - Special issue on multistrategy learning
Learning logic programs by using the product homomorphism method
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Learning atomic formulas with prescribed properties
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Complexity and expressive power of logic programming
ACM Computing Surveys (CSUR)
Phase Transitions in Relational Learning
Machine Learning
On the Complexity of Single-Rule Datalog Queries
LPAR '99 Proceedings of the 6th International Conference on Logic Programming and Automated Reasoning
Mining Insurance Data at Swiss Life
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Scalability Issues in Inductive Logic Programming
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
Tailoring Representations to Different Requirements
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
On the complexity of single-rule datalog queries
Information and Computation - Special issue: ICC '99
Complexity in the case against accuracy estimation
Theoretical Computer Science
Complexity parameters for first order classes
Machine Learning
Prediction-hardness of acyclic conjunctive queries
Theoretical Computer Science - Algorithmic learning theory (ALT 2000)
Relational learning for NLP using linear threshold elements
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Relational learning via propositional algorithms: an information extraction case study
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Learnability of description logic programs
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
(Agnostic) PAC learning concepts in higher-order logic
ECML'06 Proceedings of the 17th European conference on Machine Learning
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
Learning for deep language understanding
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Inductive Logic Programming and Embodied Agents: Possibilities and Limitations
International Journal of Agent Technologies and Systems
Automatic Learning of Temporal Relations Under the Closed World Assumption
Fundamenta Informaticae - Cognitive Informatics and Computational Intelligence: Theory and Applications
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The paper gives an overview of theoretical results in the rapidly growing field of inductive logic programming (ILP). The ILP learning situation (generality model, background knowledge, examples, hypotheses) is formally characterized and various restrictions of it are discussed in the light of their impact on learnability. The two dominant models of learnability, PAC-learning and identification in the limit, are extended to take into account the ILP learning situation. Several learnability results for logic programs are then presented, both positive and negative.