Evo-Devo Algorithms: Gene-Regulation for Digital Architecture
The majority of current visual-algorithmic architecture is constricted to specific parameters that are gradient related, keeping their parts’ relation fixed within the algorithm, far away from a truly parametric modeling with a flexible topology. Recent findings around genetics and certain...
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Online Access: | https://www.mdpi.com/2313-7673/4/3/58 |
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doaj-c6c7d6c7fb9a4e2393cd3d3b9f802d6f2020-11-25T01:55:14ZengMDPI AGBiomimetics2313-76732019-08-01435810.3390/biomimetics4030058biomimetics4030058Evo-Devo Algorithms: Gene-Regulation for Digital ArchitectureDiego Navarro-Mateu0Ana Cocho-Bermejo1School of Architecture, Universitat Internacional de Catalunya, Carrer Immaculada 22, 08017 Barcelona, SpainSchool of Architecture, Universitat Internacional de Catalunya, Carrer Immaculada 22, 08017 Barcelona, SpainThe majority of current visual-algorithmic architecture is constricted to specific parameters that are gradient related, keeping their parts’ relation fixed within the algorithm, far away from a truly parametric modeling with a flexible topology. Recent findings around genetics and certain genes capable of shape conditioning (development) have succeeded in recovering the science of embryology as a valid field that connects and affects the evolutionary ecosystem, showing the existence of universal mechanisms that are present in living species, thus describing powerful strategies for generation and emergence. Therefore, a new dual discipline is justified: Evolutionary developmental biology science. Authors propose the convergence of genetics algorithms and simulated features from evolutionary developmental biology into a single data-flow that will prove itself capable of generating great diversity through a simple and flexible structure of data, commands, and polygonal geometry. For that matter, a case study through visual-algorithmic software deals with the hypothesis that for obtaining a greater emergence and design space, a simpler and more flexible approach might only be required, prioritizing hierarchical levels over complex and detailed operations.https://www.mdpi.com/2313-7673/4/3/58genetic algorithmsevolutionary developmentproto-architecturevisual programming |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Diego Navarro-Mateu Ana Cocho-Bermejo |
spellingShingle |
Diego Navarro-Mateu Ana Cocho-Bermejo Evo-Devo Algorithms: Gene-Regulation for Digital Architecture Biomimetics genetic algorithms evolutionary development proto-architecture visual programming |
author_facet |
Diego Navarro-Mateu Ana Cocho-Bermejo |
author_sort |
Diego Navarro-Mateu |
title |
Evo-Devo Algorithms: Gene-Regulation for Digital Architecture |
title_short |
Evo-Devo Algorithms: Gene-Regulation for Digital Architecture |
title_full |
Evo-Devo Algorithms: Gene-Regulation for Digital Architecture |
title_fullStr |
Evo-Devo Algorithms: Gene-Regulation for Digital Architecture |
title_full_unstemmed |
Evo-Devo Algorithms: Gene-Regulation for Digital Architecture |
title_sort |
evo-devo algorithms: gene-regulation for digital architecture |
publisher |
MDPI AG |
series |
Biomimetics |
issn |
2313-7673 |
publishDate |
2019-08-01 |
description |
The majority of current visual-algorithmic architecture is constricted to specific parameters that are gradient related, keeping their parts’ relation fixed within the algorithm, far away from a truly parametric modeling with a flexible topology. Recent findings around genetics and certain genes capable of shape conditioning (development) have succeeded in recovering the science of embryology as a valid field that connects and affects the evolutionary ecosystem, showing the existence of universal mechanisms that are present in living species, thus describing powerful strategies for generation and emergence. Therefore, a new dual discipline is justified: Evolutionary developmental biology science. Authors propose the convergence of genetics algorithms and simulated features from evolutionary developmental biology into a single data-flow that will prove itself capable of generating great diversity through a simple and flexible structure of data, commands, and polygonal geometry. For that matter, a case study through visual-algorithmic software deals with the hypothesis that for obtaining a greater emergence and design space, a simpler and more flexible approach might only be required, prioritizing hierarchical levels over complex and detailed operations. |
topic |
genetic algorithms evolutionary development proto-architecture visual programming |
url |
https://www.mdpi.com/2313-7673/4/3/58 |
work_keys_str_mv |
AT diegonavarromateu evodevoalgorithmsgeneregulationfordigitalarchitecture AT anacochobermejo evodevoalgorithmsgeneregulationfordigitalarchitecture |
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1724984339514523648 |