An Answer Set Programming encoding of Prioritized Removed Sets Revision: Application to GIS - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Applied Intelligence Année : 2010

An Answer Set Programming encoding of Prioritized Removed Sets Revision: Application to GIS

Résumé

Geographical information systems are ones of the most important application areas of belief revision. Recently, Wurbel and colleagues (Proceedings of the seventh international conference about principles of knowledge representation and reasoning, KR2000, pp. 505-516, 2000) have applied the so-called "removed sets revision" (RSR) to the problem of assessment of water heights in a flooded valley. The application was partially satisfactory since only a small part of the valley has been handled. This paper goes one step further, and proposes an extension of (RSR) called "Prioritized Removed Sets Revision" (PRSR). We show that (PRSR) performed using answer set programming makes possible to solve a practical revision problem provided by a real application in the framework of geographical information system (GIS). We first show how PRSR can be encoded into a logic program with answer set semantics, we then present an adaptation of the smodels system devoted to efficiently compute the answer sets in order to perform PRSR. The experimental study shows that the answer set programming approach gives better results than previous implementations of RSR and in particular it allows to handle the whole valley. Lastly, some experimental studies comparing our encoding with implementations based on SAT-solvers are also provided.

Dates et versions

hal-00869357 , version 1 (03-10-2013)

Identifiants

Citer

Salem Benferhat, Jonathan Ben-Naim, Odile Papini, Eric Würbel. An Answer Set Programming encoding of Prioritized Removed Sets Revision: Application to GIS. Applied Intelligence, 2010, 32 (1), pp.60-87. ⟨10.1007/s10489-008-0135-x⟩. ⟨hal-00869357⟩
124 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More