CRIL Université d'Artois
On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts
Grégoire, Éric (CRIL Université d'Artois) | Izza, Yacine (CRIL Université d'Artois) | Lagniez, Jean-Marie (CRIL Université d'Artois)
The efficient extraction of one maximal information subset that does not conflict with multiple contxts or additional information sources is a key basic issue in many A.I. domains, especially when these contexts or sources can be mutually conflicting. In this paper, this question is addressed from a computational point of view in clausal Boolean logic. A new approach is introduced that experimentally outperforms the currently most efficient technique.