A Taxonomy for artificial embryogeny
Artificial Life
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
Generating large-scale neural networks through discovering geometric regularities
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Environment as a spatial constraint on the growth of structural form
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A study on scalable representations for evolutionary optimization of ground structures
Evolutionary Computation
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Within the evolutionary computation community, there is a strong consensus to agreed on the need of indirect representations to achieve scalability. But no such consensus has been yet found on how to design an indirect representation. An idea to build a scalable representation, is to see the phenotype to genotype mapping as an iterative transformation process: an explicit development stage. But such an approach is computationally expensive and then it relevance might be questionable. Through a simple, accessible example, optimization of a block stack overhang, it is shown that, indeed, an explicit development stage can be the only way if one wants a scalable representation and/or scalable solutions to a problem.