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EvoSpace-i: a framework for interactive evolutionary algorithms

Published: 06 July 2013 Publication History

Abstract

Evolutionary art (EvoArt) encompasses a variety of research devoted to the development of evolutionary systems that can help produce artistic artifacts in an automated or semi-automated process. Given the difficulty of evaluating subjective artistic preferences, one of the main approaches used by EvoArt researchers is interactive evolution where user input guides the search. However, despite the growth of EvoArt over recent years the research area still lacks a comprehensive software tool that can help in the development of EvoArt applications. Therefore, this work presents EvoSpace-i, an open source framework for the development of collaborative-interactive evolutionary algorithms for art and design. The main components of the framework are: (i) Evospace, a population store for the development of cloud-based evolutionary algorithms, implemented using Re-dis key-value server; and an (ii) Interactive web application where end-users collaborate in a social network sharing, collecting, rating and ultimately evolving individuals. Individuals can be presented as multimedia elements or artistic artifacts (images, animations, sound) using the Processing programming language, a development language specifically aimed at artists. EvoSpace-i is designed to be easy to use and setup, allowing researchers, and more importantly artists, to quickly develop distributed and collaborative EvoArt applications. This paper presents the main details of EvoSpace-i and two example applications to illustrate the potential of the tool.

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Cited By

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  • (2022)A Machine Learning Application Based on Giorgio Morandi Still-Life Paintings to Assist Artists in the Choice of 3D CompositionsLeonardo10.1162/leon_a_0207355:1(57-61)Online publication date: 23-Feb-2022

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cover image ACM Conferences
GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
July 2013
1798 pages
ISBN:9781450319645
DOI:10.1145/2464576
  • Editor:
  • Christian Blum,
  • General Chair:
  • Enrique Alba
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 July 2013

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Author Tags

  1. cloud-based platforms
  2. interactive evolutionary computation
  3. interactive systems

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GECCO '13
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GECCO '13: Genetic and Evolutionary Computation Conference
July 6 - 10, 2013
Amsterdam, The Netherlands

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View all
  • (2022)A Machine Learning Application Based on Giorgio Morandi Still-Life Paintings to Assist Artists in the Choice of 3D CompositionsLeonardo10.1162/leon_a_0207355:1(57-61)Online publication date: 23-Feb-2022

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