Evo-devo strategies for generative architecture: colour-based patterns in polygon meshes
Author
Navarro-Mateu, Diego
Cocho-Bermejo, Ana
Publication date
2020ISSN
2313-7673
Abstract
Parametric design in architecture is often pigeonholed by its own definition and computational complexity. This article explores the generative capacity to integrate patterns and flows analogous to evolutionary developmental biology (Evo-Devo) strategies to develop emergent proto-architecture. Through the use of coloured patterns (genotype) and the modification of polygonal meshes (phenotype), a methodological proposal is achieved that is flexible to changes and personalization, computationally efficient, and includes a wide range of typologies. Both the process and the result are oriented towards computational lightness for a future and better integration of the workflow in genetic algorithms. Flow-based programming is used to replicate genetic properties such as multifunctionality, repeatability and interchangeability. The results reinforce the biological strategies against other more computationally abstract ones and successfully execute the parallels of universal mechanisms in Evo-Devo that are present in life.
Document Type
Article
Document version
Published version
Language
English
Subject (CDU)
72 - Architecture
Keywords
Arquitectura
Algorismes computacionals
Programació genètica (Informàtica)
Arquitectura
Algoritmos computacionales
Programación genética (Informática)
Architecture
Algorithms
Genetic programming (Computer science)
Pages
18
Publisher
MDPI
Collection
5;2
Is part of
Biomimetics
Citation
Navarro-Mateu, Diego; Cocho-Bermejo, Ana. Evo-devo strategies for generative architecture: colour-based patterns in polygon meshes. Biomimetics, 2020, 5(23), p. 1-18. Disponible en: <https://www.mdpi.com/2313-7673/5/2/23>. Fecha de acceso: 16 jul. 2020. DOI: 10.3390/biomimetics5020023
This item appears in the following Collection(s)
- Arquitectura [26]
Rights
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/