Scalable Understanding: Navigation Approaches for Answer Sets

Sarah Alice GagglSarah Alice Gaggl

Slides

Sarah Alice Gaggl
Scalable Understanding: Navigation Approaches for Answer Sets
Invited talk at the Artificial Intelligence Group (AIG) at the FernUnversität in Hagen, October 2022

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Bibtex

KurzfassungAbstract
Answer Set Programming (ASP) is a formalism to model and solve combinatorial search problems efficiently.
However, in practical applications, such as product configuration, the solution space can be incomprehensible, meaning that there are millions of solutions up-to an unknown number. To still be able to reach an understanding of the answer set space, we propose navigation approaches to either identify characteristics of certain answer sets or to reach subspaces that fulfill desirable criteria.
In this talk we will highlight our recent developments.
Bemerkung: Note: virtual
Projekt:Project: CPEC, NAVAS
Forschungsgruppe:Research Group: Logische Programmierung und ArgumentationLogic Programming and Argumentation

@misc{G2022,
  author = {Sarah Alice Gaggl},
  title  = {Scalable Understanding: Navigation Approaches for Answer Sets},
  year   = {2022},
  month  = {October}
}