Evaluation Techniques and Systems for Answer Set Programming: a Survey

Martin Gebser, Nicola Leone, Marco Maratea, Simona Perri, Francesco Ricca, Torsten Schaub

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

Survey track. Pages 5450-5456.

https://doi.org/10.24963/ijcai.2018/769

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Abstract

Answer set programming (ASP) is a prominent knowledge representation and reasoning paradigm that found both industrial and scientific applications. The success of ASP is due to the combination of two factors: a rich modeling language and the availability of efficient ASP implementations. In this paper we trace the history of ASP systems, describing the key evaluation techniques and their implementation in actual tools.

Keywords

  • Knowledge Representation and Reasoning: Logics for Knowledge Representation
  • Constraints and SAT: Constraints: Solvers and Tools
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