Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
An Analysis of the Causes of Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Classifiers that approximate functions
Natural Computing: an international journal
A Randomized ANOVA Procedure for Comparing Performance Curves
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Extending XCSF beyond linear approximation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Classifier fitness based on accuracy
Evolutionary Computation
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
An analysis of matching in learning classifier systems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Classifier Conditions Using Gene Expression Programming
Learning Classifier Systems
Learning sensorimotor control structures with XCSF: redundancy exploitation and dynamic control
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
A first assessment of the use of extended relational alphabets in accuracy classifier systems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Towards efficient and effective negative selection algorithm: a convex hull representation scheme
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
To handle real valued input in XCS: using fuzzy hyper-trapezoidal membership in classifier condition
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Towards final rule set reduction in XCS: a fuzzy representation approach
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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This papers presents a novel representation of classifier conditions based on convex hulls. A classifier condition is represented by a sets of points in the problem space. These points identify a convex hull that delineates a convex region in the problem space. The condition matches all the problem instances inside such region. XCSF with convex conditions is applied to function approximation problems and its performance is compared to that of XCSF with interval conditions. The comparison shows that XCSF with convex hulls converges faster than XCSF with interval conditions. However, convex conditions usually do not produce more compact solutions.