Prolog programming for artificial intelligence
Prolog programming for artificial intelligence
The Utility of Knowledge in Inductive Learning
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Algorithmic Program DeBugging
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Two Methods for Improving Inductive Logic Programming Systems
ECML '93 Proceedings of the European Conference on Machine Learning
ECML '93 Proceedings of the European Conference on Machine Learning
Tutorial on Termination of Logic Programs
META-92 Proceedings of the 3rd International Workshop on Meta-Programming in Logic
IEEE Intelligent Systems
LIME: A System for Learning Relations
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
The Knowledge Engineering Review
Graph-based Relational Learning with Application to Security
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Induction of first-order decision lists: results on learning the past tense of English verbs
Journal of Artificial Intelligence Research
Learning semantic definitions of online information sources
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Towards flexible multi-agent decision-making under time pressure
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Learning semantic descriptions of web information sources
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Learning an ensemble of semantic parsers for building dialog-based natural language interfaces
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
Iems: helping users manage email
UM'03 Proceedings of the 9th international conference on User modeling
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Towards learning rules from natural texts
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
Learning closed sets of labeled graphs for chemical applications
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Graph-based Relational Learning with Application to Security
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Automatic Learning of Temporal Relations Under the Closed World Assumption
Fundamenta Informaticae - Cognitive Informatics and Computational Intelligence: Theory and Applications
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FOIL is a system for inducing function-free Horn clause definitions of relations from example and extensionally defined background relations. It demonstrates the successful application of a general to specific approach to clause induction using heuristically guided search. This paper describes the current version of FOIL, assesses its performance and notes areas for improvement. The successful application of similar methods in other systems is reviewed to demonstrate their general utility.