Rule-based Generative Systems

Rule-Based Generative Systems is a computational framework that systematically produces outputs through the application of predefined formal rules, distinguished by its reliance on explicitly encoded generative rules to constrain and direct the generation process within rule-based design and generative performance contexts.

24

Publications

1.1K

Citations

61

Authors

24

Institutions

Publications per year

2017–2026

5

Authors

61

  1. SJ
    Stephen Jay Gould

    Harvard University, United States

    2 publications · 27 citations

    2

    h-index

  2. CS
    Chunyi Sun

    Kunming Medical University, China

    2 publications · 27 citations

    2

    h-index

  3. ZQ
    Zishan Qin

    Australian National University, Australia

    2 publications · 27 citations

    2

    h-index

  4. XW
    Xinlong Wang

    Nanjing University, China

    2 publications · 27 citations

    2

    h-index

  5. JH
    Junlin Han

    Australian National University, Australia

    2 publications · 27 citations

    2

    h-index

1–5 of 61

Venues

  1. Music Perception An Interdisciplinary Journal

    1 publications · 215 citations

    1

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  2. Computer Music Journal

    1 publications · 122 citations

    1

    h-index

  3. 1

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  4. ACADIA quarterly

    1 publications · 17 citations

    1

    h-index

  5. Interface

    1 publications · 12 citations

    1

    h-index

1–5