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Environment as a spatial constraint on the growth of structural form

Published: 07 July 2007 Publication History

Abstract

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.

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  • (2015)Evolutionary Training of Robotised Architectural ElementsApplications of Evolutionary Computation10.1007/978-3-319-16549-3_66(819-830)Online publication date: 17-Mar-2015
  • (2014)Artificial Neurogenesis: An Introduction and Selective ReviewGrowing Adaptive Machines10.1007/978-3-642-55337-0_1(1-60)Online publication date: 5-Jun-2014
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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 07 July 2007

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Author Tags

  1. artificial embryogeny
  2. computational development
  3. developmental algorithms
  4. environment
  5. evolutionary computation
  6. structure
  7. topological optimization
  8. truss

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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  • (2016)Discrete Planar Truss Optimization by Node Position Variation Using Grammatical EvolutionIEEE Transactions on Evolutionary Computation10.1109/TEVC.2015.250284120:4(577-589)Online publication date: Aug-2016
  • (2015)Evolutionary Training of Robotised Architectural ElementsApplications of Evolutionary Computation10.1007/978-3-319-16549-3_66(819-830)Online publication date: 17-Mar-2015
  • (2014)Artificial Neurogenesis: An Introduction and Selective ReviewGrowing Adaptive Machines10.1007/978-3-642-55337-0_1(1-60)Online publication date: 5-Jun-2014
  • (2013)Evolution of a digital organism playing Go2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)10.1109/EAIS.2013.6604115(130-137)Online publication date: Apr-2013
  • (2012)Mechanisms for Complex Systems Engineering Through Artificial DevelopmentMorphogenetic Engineering10.1007/978-3-642-33902-8_13(331-351)Online publication date: 13-Dec-2012
  • (2012)Genome parameters as information to forecast emergent developmental behaviorsProceedings of the 11th international conference on Unconventional Computation and Natural Computation10.1007/978-3-642-32894-7_18(186-197)Online publication date: 3-Sep-2012
  • (2011)On the correlations between developmental diversity and genomic compositionProceedings of the 13th annual conference on Genetic and evolutionary computation10.1145/2001576.2001779(1507-1514)Online publication date: 12-Jul-2011
  • (2011)Robustness and the Halting Problem for Multicellular Artificial OntogenyIEEE Transactions on Evolutionary Computation10.1109/TEVC.2011.212596915:3(387-404)Online publication date: 1-Jun-2011
  • (2010)Artificial Embryogeny for Network Structures and its application for a Robot Generation TaskTransactions of the Japanese Society for Artificial Intelligence10.1527/tjsai.25.42325(423-432)Online publication date: 2010
  • (2010)Computational evolutionary embryogenyIEEE Transactions on Evolutionary Computation10.1109/TEVC.2009.203043814:2(301-325)Online publication date: 1-Apr-2010
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