Generative Aesthetics

Generative Aesthetics is an academic construct that denotes the systematic study and formalization of aesthetic principles and creative decision-making processes inherent in algorithmically generated video art, distinguishing it from general aesthetics by its focus on dynamic, rule-based, and autonomous systems that produce visual and temporal form.

26

Publications

1.1K

Citations

49

Authors

31

Institutions

Publications per year

2017–2026

12

Authors

49

  1. AD
    Alan Dorin

    Monash University, Australia

    4 publications · 268 citations

    4

    h-index

  2. JM
    Jon McCormack

    Monash University, Australia

    3 publications · 143 citations

    3

    h-index

  3. AT
    Artem Timoshenko

    Massachusetts Institute of Technology, United States

    2 publications · 108 citations

    2

    h-index

  4. KZ
    Kang Zhang

    The University of Texas at Dallas, United States

    2 publications · 45 citations

    2

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  5. GM
    Gordon Monro

    Monash University, Australia

    2 publications · 131 citations

    2

    h-index

1–5 of 49

Venues

  1. Leonardo

    3 publications · 130 citations

    3

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  2. Digital Creativity

    2 publications · 269 citations

    2

    h-index

  3. Advanced Engineering Informatics

    1 publications · 28 citations

    2

    h-index

  4. Marketing Science

    1 publications · 86 citations

    1

    h-index

  5. Computers & Graphics

    1 publications · 20 citations

    1

    h-index

1–5