Artificial Ontogeny for Truss Structure Design

Alexandre Devert 1, 2 Nicolas Bredeche 1, 2 Marc Schoenauer 1, 2
2 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : This paper introduces an approach based on Artificial Embryogeny for truss design to address the problem of finding the best truss structure for a given loading. In this setup, the basic idea is to optimize the size and length of beams in a truss through the actions of a set of cells that are distributed over the very truss structure. Given information at the mechanical level (beam strain), each cell controller is able to modify the local truss structure (beam size and length) during a developmental process. The advantage of such a method relies on the idea that a template cell controller is duplicated over all cells, keeping the optimization search space very low, while each cell may act in a different manner depending on local information. This approach is demonstrated on a classical benchmark, the cantilever: resulting organisms are shown to provide very interesting and unique properties regarding reuse of optimized genotypes in noisy or higher-dimension settings.
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Communication dans un congrès
Workshop on Spatial Computing (SCW) at the second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2008, Venice, Italy. 2008
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Alexandre Devert, Nicolas Bredeche, Marc Schoenauer. Artificial Ontogeny for Truss Structure Design. Workshop on Spatial Computing (SCW) at the second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2008, Venice, Italy. 2008. 〈inria-00337053〉

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