Abstract
Evolutionary hardware design reveals the potential to provide autonomous systems with self-adaptation properties. We first outline an architectural concept for an intrinsically evolvable embedded system that adapts to slow changes in the environment by simulated evolution, and to rapid changes in available resources by switching to preevolved alternative circuits. In the main part of the paper, we treat evolutionary circuit design as a multi-objective optimization problem and compare two multi-objective optimizers with a reference genetic algorithm. In our experiments, the best results were achieved with TSPEA2, an optimizer that prefers a single objective while trying to maintain diversity.
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Kaufmann, P., Platzner, M. (2007). Toward Self-adaptive Embedded Systems: Multi-objective Hardware Evolution. In: Lukowicz, P., Thiele, L., Tröster, G. (eds) Architecture of Computing Systems - ARCS 2007. ARCS 2007. Lecture Notes in Computer Science, vol 4415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71270-1_15
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DOI: https://doi.org/10.1007/978-3-540-71270-1_15
Publisher Name: Springer, Berlin, Heidelberg
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