Efficient Explanations for Knowledge Compilation Languages - Méthodes et Ingénierie des Langues, des Ontologies et du Discours Access content directly
Preprints, Working Papers, ... Year : 2021

Efficient Explanations for Knowledge Compilation Languages

Abstract

Knowledge compilation (KC) languages find a growing number of practical uses, including in Constraint Programming (CP) and in Machine Learning (ML). In most applications, one natural question is how to explain the decisions made by models represented by a KC language. This paper shows that for many of the best known KC languages, well-known classes of explanations can be computed in polynomial time. These classes include deterministic decomposable negation normal form (d-DNNF), and so any KC language that is strictly less succinct than d-DNNF. Furthermore, the paper also investigates the conditions under which polynomial time computation of explanations can be extended to KC languages more succinct than d-DNNF.
Fichier principal
Vignette du fichier
paper.pdf (656.4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03311518 , version 1 (01-08-2021)

Licence

Attribution

Identifiers

  • HAL Id : hal-03311518 , version 1

Cite

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Martin Cooper, Nicholas Asher, et al.. Efficient Explanations for Knowledge Compilation Languages. 2021. ⟨hal-03311518⟩
120 View
30 Download

Share

Gmail Facebook X LinkedIn More