The algorithmic beauty of plants
The algorithmic beauty of plants
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Evolutionary Design of Arbitrarily Large Sorting Networks Using Development
Genetic Programming and Evolvable Machines
Evolutionary computation and structural design: A survey of the state-of-the-art
Computers and Structures
An evolvability-enhanced artificial embryogeny for generating network structures
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Measures of complexity for artificial embryogeny
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolution, development and learning using self-modifying cartesian genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
When and why development is needed: generative and developmental systems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Augmenting artificial development with local fitness
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Computational evolutionary embryogeny
IEEE Transactions on Evolutionary Computation
On the correlations between developmental diversity and genomic composition
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Genome parameters as information to forecast emergent developmental behaviors
UCNC'12 Proceedings of the 11th international conference on Unconventional Computation and Natural Computation
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We explore the use of the developmental environment as a spatial constraint on a model of Artificial Embryogeny, applied to the growth of structural forms. A Deva model is used to translate genotype to phenotype, allowing a Genetic Algorithm to evolve Plane Trusses. Genomes are expressed in one of several developmental environments, and selected using a fitness function favouring stability, height, and distribution of pressure. Positive results are found in nearly all cases, demonstrating that environment can be used as an effective spatial constraint on development. Further experiments take genomes evolved in some environment and transplant them into different environments, or re-grow them at different phenotypic sizes; It is shown that while some genomes are highly specialized for the particular environment in which they evolved, others may be re-used in a different context without significant re-design, retaining the majority of their original utility. This strengthens the notion that growth via Artificial Embryogeny can be resistant to perturbations in environment, and that good designs may be re-used in a variety of contexts.