Adaptation of length in a nonstationary environment
Computer Science, Interdisciplinary Applications; Computer Science, ; Theory & Methods
In this paper, we examine the behavior of a variable length CA in a nonstationary problem environment. Results indicate that a variable length GA is better able to adapt to changes than a fixed length GA. Closer examination of the evolutionary dynamics reveals that a variable length GA can in fact take advantage of its variable length representation to exploit good quality building blocks after a change in the problem environment.
Genetic and Evolutionary Computation - Gecco 2003, Pt Ii, Proceedings
"Adaptation of length in a nonstationary environment" (2003). Faculty Bibliography 2000s. 4151.