Improve and Compact Population in XCSFCA using Polynomial Equation
XCS is a rule-based evolutionary online learning system. XCSFCA is an extension of XCS where compute continuous actions directly from input states. In XCSFCA, computed actions of a classifier, demonstrated as a straight lines. But in very problems, the desired best action curves are not linear and there are arched; therefore a system with linear action computation needs a large population. This paper studies a new method for compute continuous actions directly from input states. In new proposed method action computes by polynomial equation. Consequently each classifier represents a nonlinear action curve and the classifiers are more generalized. In comparison with XCSFCA, our method proves to be more efficient and smaller population size.
Keywords: XCS, XCSF, XCSFCA, continuous action, polynomial equation
Download Full-Text
ABOUT THE AUTHORS
Saeid Goodarzian
Ali Hamzeh
Sattar Hashemi
Saeid Goodarzian
Ali Hamzeh
Sattar Hashemi