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

Authors

626

  1. TS
    Torsten Schaub

    University of Potsdam, Germany

    54 publications · 3K citations

    27

    h-index

  2. TE
    Thomas Eiter

    TU Wien, Austria

    38 publications · 3K citations

    23

    h-index

  3. HT
    Hans Tompits

    TU Wien, Austria

    22 publications · 1.7K citations

    19

    h-index

  4. MG
    Martin Gebser

    University of Potsdam, Germany

    32 publications · 2.2K citations

    19

    h-index

  5. SW
    Stefan Woltran

    TU Wien, Austria

    32 publications · 1K citations

    17

    h-index

1–5 of 626

Venues

  1. Theory and Practice of Logic Programming

    95 publications · 3.6K citations

    33

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 26 publications · 658 citations

    14

    h-index

  3. Artificial Intelligence

    14 publications · 1.5K citations

    12

    h-index

  4. ArXiv.org

    Repository · 11 publications · 413 citations

    11

    h-index

  5. arXiv (Cornell University)

    Repository · 18 publications · 306 citations

    11

    h-index

1–5