Illinois Genetic Algorithms Laboratory

Wilson, S.W. (2001)
TR No.: 2001027 | Download PDF | Download PS

Abstract:
A classifier system, XCSF, is introduced in which the prediction
estimation mechanism is used to learn approximations to functions.
The addition of weight vectors to the classifiers allows
piecewise-linear approximation, where the classifier’s
prediction is calculated instead of being a fixed scalar. Results
on functions of up to six dimensions show high accuracy.
The idea of calculating the prediction leads to the concept of
a generalized classifier in which the payoff prediction approximates
the environmental payoff function over a subspace defined by
the classifier condition and an action restriction specified in the
classifier, permitting continuous-valued actions.