Representative Answer Sets: Collecting Something of Everything

Elisa BöhlElisa Böhl, Sarah Alice GagglSarah Alice Gaggl, Dominik RusovacDominik Rusovac

Elisa Böhl, Sarah Alice Gaggl, Dominik Rusovac
Representative Answer Sets: Collecting Something of Everything
In Kobi Gal, Ann Nowé, Grzegorz J. Nalepa, Roy Fairstein, Roxana Radulescu, eds., Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), 271--278, September 2023. IOS Press

Details
Bibtex

KurzfassungAbstract
Answer set programming (ASP) is a popular problem solving paradigm with
applications in planning and configuration. In practice, the number of answer sets can be overwhelmingly high, which naturally causes interest in a concise characterisation of the solution space in terms of representative answer sets. We establish a notion of representativeness that refers to the entropy of specified target atoms within a collection of answer sets. Accordingly, we propose different approaches for collecting such representative answer sets, based on answer set navigation. Finally, we conduct experiments using our prototypical implementation, which
reveals promising results.
Weitere Informationen unter:Further Information: Link
Projekt:Project: NAVAS
Forschungsgruppe:Research Group: Logische Programmierung und ArgumentationLogic Programming and Argumentation

@inproceedings{BGR2023,
  author    = {Elisa B{\"{o}}hl and Sarah Alice Gaggl and Dominik Rusovac},
  title     = {Representative Answer Sets: Collecting Something of Everything},
  editor    = {Kobi Gal and Ann Now{\'{e}} and Grzegorz J. Nalepa and Roy
               Fairstein and Roxana Radulescu},
  booktitle = {Proceedings of the 26th European Conference on Artificial
               Intelligence (ECAI 2023)},
  publisher = {IOS Press},
  year      = {2023},
  month     = {September},
  pages     = {271--278},
  doi       = {10.3233/FAIA230280}
}