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GECCO
2005
Springer

Understanding cooperative co-evolutionary dynamics via simple fitness landscapes

9 years 6 months ago
Understanding cooperative co-evolutionary dynamics via simple fitness landscapes
Cooperative co-evolution is often used to solve difficult optimization problems by means of problem decomposition. Its performance for such tasks can vary widely from good to disappointing. One of the reasons for this is that attempts to improve co-evolutionary performance using traditional EC analysis techniques often fail to provide the necessary insights into the dynamics of co-evolutionary systems, a key factor affecting performance. In this paper we use two simple fitness landscapes to illustrate the importance of taking a dynamical systems approach to analyzing co-evolutionary algorithms in order to understand them better and to improve their problem solving performance. Categories and Subject Descriptors: I.2.m [Artificial Intelligence]: Evolutionary Computation General Terms: Algorithms.
Elena Popovici, Kenneth A. De Jong
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Elena Popovici, Kenneth A. De Jong
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