The enigma of complexity

Jon McCormack, Camilo Cruz Gambardella, Andy Lomas

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

In this paper we examine the concept of complexity as it applies to generative art and design. Complexity has many different, discipline specific definitions, such as complexity in physical systems (entropy), algorithmic measures of information complexity and the field of “complex systems”. We apply a series of different complexity measures to three different generative art datasets and look at the correlations between complexity and individual aesthetic judgement by the artist (in the case of two datasets) or the physically measured complexity of 3D forms. Our results show that the degree of correlation is different for each set and measure, indicating that there is no overall “better” measure. However, specific measures do perform well on individual datasets, indicating that careful choice can increase the value of using such measures. We conclude by discussing the value of direct measures in generative and evolutionary art, reinforcing recent findings from neuroimaging and psychology which suggest human aesthetic judgement is informed by many extrinsic factors beyond the measurable properties of the object being judged.

Original languageEnglish
Title of host publication10th International Conference, EvoMUSART 2021 Held as Part of EvoStar 2021 Virtual Event, April 7–9, 2021 Proceedings
EditorsJuan Romero, Tiago Martins, Nereida Rodríguez-Fernández
Place of PublicationCham Switzerland
PublisherSpringer
Pages203-217
Number of pages15
ISBN (Electronic)9783030729141
ISBN (Print)9783030729134
DOIs
Publication statusPublished - 2021
EventInternational Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2021 - Virtual, Online, Spain
Duration: 7 Apr 20219 Apr 2021
Conference number: 10th
https://link.springer.com/book/10.1007/978-3-030-72914-1 (Proceedings)
http://www.evostar.org/2021/evomusart/ (Website)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12693 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2021
Abbreviated titleEvoMUSART 2021
Country/TerritorySpain
CityVirtual, Online
Period7/04/219/04/21
Internet address

Keywords

  • Aesthetic measure
  • Complexity
  • Evolutionary art
  • Fitness measure
  • Generative art
  • Generative design

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