Deep Permutation Design: A new potential artificial intelligence-based design methodology

Autor:	Kostas Terzidis, Filippo Fabrocini, Hyejin Lee, Louis Daumard
Rok vydání:	2023
Předmět:	Visual Arts and Performing Arts Engineering (miscellaneous) Music Computer Science Applications
Zdroj:	Leonardo. :1-10
ISSN:	1530-9282 0024-094X
DOI:	10.1162/leon_a_02359
Popis:	An artificial intelligence–based design methodology is presented based on permutations and neural networks. Elements are combined in all possible ways to form all possible design solutions, and a neural network extracts the best solution after being trained on either objective or subjective criteria. This methodology is projected to have many applications in fashion, architecture, music, storytelling, cooking, or any other design or art field that can be represented as a set of permutations.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c00765469867cb66bfe341cc3480a42 https://doi.org/10.1162/leon_a_02359 Zobrazit plný text záznamu