Adaptation on the Evolutionary Time Scale: A Working Hypothesis and Basic Experiments

In the pertinent literature, an ongoing discussion can be found about whether evolutionary algorithms are better suited for optimization or adaptation. Unfortunately, the pertinent literature does not o er a de nition of the di erence between adaptation and optimization. As a working hypothesis, this paper proposes adaptation as tracking the moving optimum of a dynamically changing tness function as opposed to optimization as nding the optimum of a static tness function. The results presented in this paper suggest that providing enough variation among the population members and applying a selection scheme is sufcient for adaptation. The resulting performance, however, depends on the problem, the selection scheme, the variation operators, as well as possibly other factors.

• Type: Conference
• Year: 1997
• Where: AE
• Authors: Ralf Salomon, Peter Eggenberger
• Keywords: AE 1997, Artificial Intelligence, Paper Proposes Adaptation, Pertinent Literature, Selection Scheme