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Coevolutionary Convergence to Global Optima
Lothar M. Schmitt
The University of Aizu,
Aizu-Wakamatsu City,
Fukushima Prefecture 965-8580, Japan
lothar@u-aizu.ac.jp
Abstract.
We discuss a theory for a realistic, applicable scaled genetic
algorithm (GA) which converges asymptoticly to global optima in a
coevolutionary setting involving two species.
It is shown for the first time that coevolutionary arms races
yielding global optima can be implemented successfully in a
procedure similar to simulated annealing.
Keywords: Coevolution; convergence of genetic algorithms; simulated annealing; genetic programming.
LNCS 2723, p. 373 f.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003