Answer Set Programming
Answer Set Programming is a declarative logic programming paradigm based on the stable model semantics, in which the solutions to a problem are represented as answer sets—maximal consistent sets of literals satisfying a set of rules—distinguishing it from other rule-based formalisms by its non-monotonic reasoning capabilities and support for default negation.
493
Publications
20.3K
Citations
626
Authors
247
Institutions
Publications per year
2017–2026
109
493
Potassco: The Potsdam Answer Set Solving Collection
Martin Gebser, Benjamin Kaufmann, Roland Kaminski et al. · AI Communications · 2011 · 471 citations
Answer set programming and plan generation
Vladimir Lifschitz · Artificial Intelligence · 2002 · 451 citations
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247

TU Wien
Vienna, Austria
33 h-index
213 publications
11K citations
University of Potsdam
Potsdam, Germany
29 h-index
144 publications
8.7K citations

University of Calabria
Rende, Italy
27 h-index
111 publications
5.7K citations
Arizona State University
Tempe, United States
22 h-index
61 publications
2.5K citations

New Mexico State University
Las Cruces, United States
14 h-index
35 publications
1.2K citations
Aalto University
Espoo, Finland
13 h-index
27 publications
952 citations

University of Genoa
Genoa, Italy
13 h-index
21 publications
1K citations
The University of Texas at Austin
Austin, United States
13 h-index
24 publications
2.3K citations
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95 publications · 3.6K citations
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Conference · 26 publications · 658 citations
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14 publications · 1.5K citations
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Repository · 11 publications · 413 citations
11
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Repository · 18 publications · 306 citations
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