Abstract
The idea of evolutionary friendliness recognizes that problem representations have a significant impact on the performance of evolutionary algorithms. There are two aspects of these representations. Different solution schemes exploit different natural symmetries. Very commonly, problems also possess symmetries that are determined by the coordinate systems used to represent them. Solution symmetries are typically specified by the user and are not allowed to evolve. The problem coordinate system is again typically chosen by the user and not evolved. In this first paper, the most appropriate solution symmetry is evolved. In the second paper, the coordinate system is evolved. In this paper, common detection problems with decision boundaries that possess special symmetries are solved using an evolutionary programming (EP) framework that is capable of exploiting these symmetries to quickly generate solutions. In particular, neural networks possessing appropriate symmetries are evolved by optimizing both their bases and their parameters. Simulation results indicate that the EP procedure is capable of selecting appropriate basis functions for different regions of the input space as well as optimizing the associated set of parameters.
Funded in part by the California Institute for Energy Efficiency Project on Diagnostics for Building Commissioning And Operation. The authors are indebted to Lee Eng Lock for many hours of very fruitful tutelage and conversation regarding proper ways to visualize detection of anomalous behavior in large class A building HVAC systems.
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© 1998 Springer-Verlag Berlin Heidelberg
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Sebald, A.V., Chellapilla, K. (1998). On making problems evolutionarily friendly part 1: Evolving the most convenient representations. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040780
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DOI: https://doi.org/10.1007/BFb0040780
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