How Potential BLFs Can Help to Decide under Incomplete Knowledge

Florence Dupin de Saint-Cyr (1, 2) , Romain Guillaume (1, 3)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 UT3 - Université Toulouse III - Paul Sabatier
3 UT2J - Université Toulouse - Jean Jaurès

In a Bipolar Leveled Framework (BLF) [7], the comparison of two candidates is done on the basis of the decision principles and inhibitions which are validated given the available knowledge-bases associated with each candidate. This article defines a refinement of the rules for comparing candidates by using the potential-BLFs which can be built according to what could additionally be learned about the candidates. We also propose a strategy for selecting the knowledge to acquire in order to better discriminate between candidates.

Mots clés: Arguments; Incomplete knowledge; Bipolarity; Qualitative decision making

Domaines: Logique en informatique [cs.LO]

Florence Dupin de Saint-Cyr, Romain Guillaume. How Potential BLFs Can Help to Decide under Incomplete Knowledge. 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Jun 2018, Cadiz, Spain. pp.86-98, ⟨10.1007/978-3-319-91479-4_8⟩. ⟨hal-02319705⟩