A pattern based evolutionary approach to prediction computation in XCSF

Authors:
Ali Hamzeh;Adel Rahmani
Affiliations:
Department of Computer Engineering, Iran University of Science and Technology, Tehran, Iran;Department of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

Citing 4
Cited 0

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Classifiers that approximate functions

Natural Computing: an international journal
Classifier fitness based on accuracy

Evolutionary Computation
An evolutionary function approximation approach to compute prediction in XCSF

ECML'05 Proceedings of the 16th European conference on Machine Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

XCSF is a new version of XCS with the ability of computing the environmental rewards. In the early versions of XCSF, this computation was done by approximating the coefficients of the associated polynomial reward functions. However, recent researches show that this approximation method suffers from some significant drawbacks such as input range dependency. In this paper, we propose a new method to approximate the reward functions using Genetic Algorithms. Our proposed method uses a new representation scheme for chromosomes and some newly introduced pattern based operators which are adapted for function approximation.