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Modularity and symmetry in computational embryogeny

Yogev, Or and Shapiro, Andrew A. and Antonsson, Erik K. (2008) Modularity and symmetry in computational embryogeny. In: GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation. ACM , New York, NY, pp. 1151-1152. ISBN 978-1-60558-130-9. https://resolver.caltech.edu/CaltechAUTHORS:20170109-154237488

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Abstract

Modularity and symmetry are two properties observed in almost every engineering and biological structure. The origin of these properties in nature is still unknown. Yet, as engineers we tend to generate designs which share these properties. In this paper we will report on the origin of these properties in three dimensional evolved structures (phenotypes). The phenotypes were evolved in an evolutionarydevelopmental model of biological structures. The phenotypes were grown under a high volatility stochastic environment. The phenotypes have evolved to function within the environment using the very basic requirements. Even though neither modularity nor symmetry have been directly imposed as part of the requirements, the phenotypes were able to generate these properties after only a few hundred generations. These results may suggest that modularity and symmetry are both very fundamental properties that develop during the early stages of evolution. This result may give insight to the origin of both modularity and symmetry in biological organisms.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/1389095.1389323DOIArticle
http://dl.acm.org/citation.cfm?doid=1389095.1389323PublisherArticle
Additional Information:Copyright is held by the author/owner(s). Our thanks to ACM SIGCHI for allowing us to modify templates they had developed. The research described in this paper was sponsored by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration as part of the Ultra-Reliability Program.
Funders:
Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
Subject Keywords:Algorithms, Design, Genetic Algorithm, Indirect Encoding, Stresses, Finite Element, Artificial Cell
Classification Code:I.2.1 1 Distributed Artificial Intelligence [Intelligent agents]
Record Number:CaltechAUTHORS:20170109-154237488
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170109-154237488
Official Citation:Or Yogev, Andrew A. Shapiro, and Erik K. Antonsson. 2008. Modularity and symmetry in computational embryogeny. In Proceedings of the 10th annual conference on Genetic and evolutionary computation (GECCO '08), Maarten Keijzer (Ed.). ACM, New York, NY, USA, 1151-1152. DOI=http://dx.doi.org/10.1145/1389095.1389323
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73354
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:10 Jan 2017 04:56
Last Modified:03 Oct 2019 16:27

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