New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Learning structured concepts using genetic algorithms
ML92 Proceedings of the ninth international workshop on Machine learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
DOGMA: A GA-Based Relational Learner
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Refinement Operators Can Be (Weakly) Perfect
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Search-intensive concept induction
Evolutionary Computation
Application of Pruning Techniques for Propositional Learning to Progol
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
A Genetic Algorithm for Propositionalization
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Hybrid Learning of Ontology Classes
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
A Note on Refinement Operators for IE-Based ILP Systems
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Learning theories using estimation distribution algorithms and (reduced) bottom clauses
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
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A framework for combining Genetic Algorithms with ILP methods is introduced and a novel binary representation and relevant genetic operators are discussed. It is shown that the proposed representation encodes a subsumption lattice in a complete and compact way. It is also shown that the proposed genetic operators are meaningful and can be interpreted in ILP terms such as lgg (least general generalization) and mgi (most general instance). These operators can be used to explore a subsumption lattice efficiently by doing binary operations (e.g. and/or). An implementation of the proposed framework is used to combine Inverse Entailment of CProgol with a genetic search.