On using genetic algorithms to search program spaces
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Improved training via incremental learning
Proceedings of the sixth international workshop on Machine learning
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Machine Learning
Genetic Plans and the Probabilistic Learning System: Synthesis and Results
Proceedings of the 1st International Conference on Genetic Algorithms
Triggered Rule Discovery in Classifier Systems
Proceedings of the 3rd International Conference on Genetic Algorithms
Evolution of Multi-adaptive Discretization Intervals for a Rule-Based Genetic Learning System
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A Learning Classifier Systems Bibliography
Learning Classifier Systems, From Foundations to Applications
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Evolving Behaviors for Cooperating Agents
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Extracting User Profiles from E-mails Using the Set-Oriented Classifier
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Using coverage as a model building constraint in learning classifier systems
Evolutionary Computation
Search-intensive concept induction
Evolutionary Computation
An analysis of the “universal suffrage” selection operator
Evolutionary Computation
Learning Classifier Systems: Looking Back and Glimpsing Ahead
Learning Classifier Systems
Substructural Surrogates for Learning Decomposable Classification Problems
Learning Classifier Systems
Performance and efficiency of memetic pittsburgh learning classifier systems
Evolutionary Computation
A class decomposition approach for GA-based classifiers
Engineering Applications of Artificial Intelligence
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Tournament selection: stable fitness pressure in XCS
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Binary rule encoding schemes: a study using the compact classifier system
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
COGIN: symbolic induction with genetic algorithms
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
IEEE Transactions on Evolutionary Computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Mining data streams with concept drifts using genetic algorithm
Artificial Intelligence Review
Prediction rule generation of MHC class i binding peptides using ANN and GA
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Rule generation using NN and GA for SARS-CoV cleavage site prediction
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Intrusion detection based on immune clonal selection algorithms
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Post-processing operators for decision lists
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Recursive Learning of Genetic Algorithms with Task Decomposition and Varied Rule Set
International Journal of Applied Evolutionary Computation
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In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a system GABEL which continually learns and refines concept classification rules from its interaction with the environment. The performance of the system is measured on a set of concept learning problems and compared with the performance of two existing systems: ID5R and C4.5. Preliminary results support that, despite minimal system bias, GABIL is an effective concept learner and is quite competitive with ID5R and C4.5 as the target concept increases in complexity.