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Title:
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Evo-devo algorithms: gene-regulation for digital architecture
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Author:
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Navarro-Mateu, Diego; Cocho-Bermejo, Ana
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Notes:
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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. |
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Subject(s):
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-Algoritmos computacionales
-Arquitectura
-Genètica--Tècnica
-Algorismes computacionals
-Algorithms--Data processing
-Genetics
-Genética
-Genètica
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Rights:
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© 2019 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/). |
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Document type:
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Article
Article - Accepted version |
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Published by:
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Multidisciplinary Digital Publishing Institute
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