Constraint-driven Generation
Constraint-Driven Generation is a generative methodology in which the production of outputs is systematically governed by predefined constraints that restrict the solution space to ensure adherence to specific structural, semantic, or functional requirements.
110
Publications
3.6K
Citations
302
Authors
124
Institutions
Publications per year
2017–2026
36
Parents
110
Markov constraints: steerable generation of Markov sequences
François Pachet, Pierre Roy · Constraints · 2010 · 92 citations · Full text
Multi-step multi-sensor hider-seeker games
Erik Halvorson, Vincent Conitzer, Ronald Parr · 2009 · 87 citations
1–5 of 110
302
University of California, Berkeley, United States
4 publications · 141 citations
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124
The University of Texas at Austin
Austin, United States
7 h-index
7 publications
253 citations
University of Michigan
Ann Arbor, United States
5 h-index
11 publications
276 citations
University of California, Berkeley
Berkeley, United States
5 h-index
16 publications
463 citations
University of Illinois Chicago
Chicago, United States
4 h-index
15 publications
388 citations
Synopsys (United States)
Mountain View, United States
4 h-index
4 publications
115 citations
Google (United States)
Mountain View, United States
4 h-index
5 publications
151 citations
Tsinghua University
Beijing, China
4 h-index
12 publications
387 citations
Motorola (United States)
Schaumburg, United States
4 h-index
5 publications
130 citations
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Repository · 3 publications · 78 citations
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TSTE · 3 publications · 122 citations
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Conference · 2 publications · 39 citations
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2 publications · 73 citations
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Conference · 2 publications · 102 citations
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