GALE
(Genetic and Artificial Life Environment) is fine-grained parallel genetic
algorithm for data mining. Its main contributions are simplicity and
its knowledge-independent model. The simplicity of
GALE relies in its fine-grained parallelism based on spreading the
population (feasible solutions to the classification task) over a 2D grid. Thus,
artificial evolution can be easily modeled in terms of neighborhood relations.
These neighborhood relations define GALE as
a massive parallel evolutionary model. On the other hand,
GALE does not constrain the knowledge representation. It can evolve
indistinctly rules, instances, partially-defined instances, and decision trees
(orthogonal, oblique, and multivariate based on nearest neighbor.)
Hope you enjoy it.
Xavier Llorà
December 6, 2002
xllora@illigal.ge.uiuc.edu