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Growth control and disease mechanisms in computational embryogeny

Yogev, Or and Shapiro, Andrew A. and Antonsson, Erik K. (2008) Growth control and disease mechanisms in computational embryogeny. In: GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation. ACM , New York, NY, pp. 871-872. ISBN 978-1-60558-130-9. https://resolver.caltech.edu/CaltechAUTHORS:20170109-153829857

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Abstract

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/1389095.1389265DOIArticle
http://dl.acm.org/citation.cfm?doid=1389095.1389265PublisherArticle
Additional Information:Copyright is held by the author/owner(s). Our thanks to ACM SIGCHI for allowing us to modify templates they 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.2.11 Distributed Artificial Intelligence [Intelligent agents]
Record Number:CaltechAUTHORS:20170109-153829857
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170109-153829857
Official Citation:Or Yogev, Andrew A. Shapiro, and Erik K. Antonsson. 2008. Growth control and disease mechanisms 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, 871-872. DOI=http://dx.doi.org/10.1145/1389095.1389265
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73353
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:10 Jan 2017 04:58
Last Modified:03 Oct 2019 16:27

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