Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Support vector regression for classifier prediction
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The XCSF classifier system in Java
ACM SIGEVOlution
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Context-dependent predictions and cognitive arm control with XCSF
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
New entropy model for extraction of structural information from XCS population
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Anticipatory Learning Classifier Systems and Factored Reinforcement Learning
Anticipatory Behavior in Adaptive Learning Systems
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
Fuzzy-UCS: a Michigan-style learning fuzzy-classifier system for supervised learning
IEEE Transactions on Evolutionary Computation
Facetwise analysis of XCS for problems with class imbalances
IEEE Transactions on Evolutionary Computation
JavaXCSF: the XCSF learning classifier system in Java
ACM SIGEVOlution
Controlling a four degree of freedom arm in 3D using the XCSF learning classifier system
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
A comparative study: function approximation with LWPR and XCSF
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Classification of BMD and ADHD patients using their EEG signals
Expert Systems with Applications: An International Journal
Towards final rule set reduction in XCS: a fuzzy representation approach
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Modularization of xcsf for multiple output dimensions
Proceedings of the 13th annual conference on Genetic and evolutionary computation
XCSF with local deletion: preventing detrimental forgetting
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Resource management and scalability of the XCSF learning classifier system
Theoretical Computer Science
Learning local linear Jacobians for flexible and adaptive robot arm control
Genetic Programming and Evolvable Machines
Filtering sensory information with XCSF: improving learning robustness and control performance
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
XCSF for prediction on emotion induced by image based on dimensional theory of emotion
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Self organizing classifiers and niched fitness
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Selection strategy for XCS with adaptive action mapping
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Comparison of two methods for computing action values in XCS with code-fragment actions
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen approximation technique develops locally optimal approximations, such as accurate classification estimates, Q-value predictions, or linear function approximations. The genetic optimization technique is designed to distribute these local approximations efficiently over the problem space. Together, the two components develop a distributed, locally optimized problem solution in the form of a population of expert rules, often called classifiers. In function approximation problems, the XCSF classifier system develops a problem solution in the form of overlapping, piecewise linear approximations. This paper shows that XCSF performance on function approximation problems additively benefits from: 1) improved representations; 2) improved genetic operators; and 3) improved approximation techniques. Additionally, this paper introduces a novel closest classifier matching mechanism for the efficient compaction of XCS's final problem solution. The resulting compaction mechanism can boil the population size down by 90% on average, while decreasing prediction accuracy only marginally. Performance evaluations show that the additional mechanisms enable XCSF to reliably, accurately, and compactly approximate even seven dimensional functions. Performance comparisons with other, heuristic function approximation techniques show that XCSF yields competitive or even superior noise-robust performance.