Towards a Knowledge Compilation Map for Heterogeneous Representation Language

Hélène Fargier (1, 2) , Pierre Marquis (3) , Alexandre Niveau (3)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 CNRS - Centre National de la Recherche Scientifique
3 CRIL - Centre de Recherche en Informatique de Lens

The knowledge compilation map introduced by Darwiche and Marquis takes advantage of a number of concepts (mainly queries, transformations, expressiveness, and succinctness) to compare the relative adequacy of representation languages to some AI problems. However, the framework is limited to the comparison of languages that are interpreted in a homogeneous way (formulæ are interpreted as Boolean functions). This prevents one from comparing, on a formal basis, languages that are close in essence, such as OBDD, MDD, and ADD. To fill the gap, we present a generalized framework into which comparing formally heterogeneous representation languages becomes feasible. In particular, we explain how the key notions of queries and transformations, expressiveness, and succinctness can be lifted to the generalized setting.

Mots clés: Knowledge compilation map; Representation languages; Heterogeneous Representation Languages

Domaines: Intelligence artificielle [cs.AI]; Informatique et langage [cs.CL]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]

Hélène Fargier, Pierre Marquis, Alexandre Niveau. Towards a Knowledge Compilation Map for Heterogeneous Representation Language. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), International Joint Conferences on Artificial Intelligence (IJCAI), Aug 2013, Beijing, China. pp.877-883. ⟨hal-04085296⟩