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.
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Publications
1.1K
Citations
61
Authors
24
Institutions
Publications per year
2017–2026
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University of Cambridge
Cambridge, United Kingdom
3 h-index
5 publications
180 citations

KTH Royal Institute of Technology
Stockholm, Sweden
2 h-index
2 publications
157 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
2 publications
446 citations
Arizona State University
Tempe, United States
1 h-index
3 publications
90 citations
The University of Texas at Austin
Austin, United States
1 h-index
1 publications
12 citations

University of Manchester
Manchester, United Kingdom
1 h-index
2 publications
26 citations
Bernstein Center for Computational Neuroscience Freiburg
Freiburg, Germany
1 h-index
3 publications
105 citations
University of Oxford
Oxford, United Kingdom
1 h-index
1 publications
15 citations
1–8 of 24
1 publications · 215 citations
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1 publications · 122 citations
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1 publications · 23 citations
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1 publications · 17 citations
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1 publications · 12 citations
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