A unified framework for structure identification

Bruno Zanuttini (1) , Jean-Jacques Hébrard (2)

1 Equipe MAD - Laboratoire GREYC - UMR6072
2 GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen

We propose a general framework for structure identification, as defined by Dechter and Pearl. It is based on the notion of prime implicate, and handles Horn, bijunctive and affine, as well as Horn-renamable formulas, for which, to our knowledge, no polynomial algorithm has been proposed before. This framework, although quite general, gives good complexity results, and in particular we get for Horn formulas the same running time and better output size than the algorithms previously known.

Domaines: Intelligence artificielle [cs.AI]

Bruno Zanuttini, Jean-Jacques Hébrard. A unified framework for structure identification. Information Processing Letters, 2002, 81 (6), pp.335-339. ⟨hal-00995240⟩