Genetic And Nongenetic Operators In ALECSYS (1992)
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| Venue: | Evolutionary Computation |
| Citations: | 26 - 12 self |
BibTeX
@ARTICLE{Dorigo92geneticand,
author = {Marco Dorigo},
title = {Genetic And Nongenetic Operators In ALECSYS},
journal = {Evolutionary Computation},
year = {1992},
volume = {1},
pages = {151--164}
}
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Abstract
It is well known that standard learning classifier systems, when applied to many different domains, exhibit a number of problems: payoff oscillation, difficult to regulate interplay between the reward system and the background genetic algorithm (GA), rule chains instability, default hierarchies instability, are only a few. ALECSYS is a parallel version of a standard learning classifier system (CS), and as such suffers of these same problems. In this paper we propose some innovative solutions to some of these problems. We introduce the following original features. Mutespec, a new genetic operator used to specialize potentially useful classifiers. Energy, a quantity introduced to measure global convergence in order to apply the genetic algorithm only when the system is close to a steady state. Dynamical adjustment of the classifiers set cardinality, in order to speed up the performance phase of the algorithm. We present simulation results of experiments run in a simulated two-dimensional...
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