Towards qualitative approaches to multi-stage decision making

Régis Sabbadin (1) , Hélène Fargier (2, 3) , Jérôme Lang (2)

1 UBIA - Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT)
2 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
3 CNRS - Centre National de la Recherche Scientifique

In this paper we propose a generalisation to multi-stage decision making of Dubois and Prade's qualitative decision theory. Our framework is a qualitative, possibilistic counterpart to Markov decision processes, and the computation of an optimal policy is done in a way similar to dynamic programming. We first study in detail the case where uncertainty about the results of actions is represented by possibility distributions and goals are described in a non-fuzzy way by a subset of the set of final states. Then we extend our framework to the case where goalness is defined fuzzily, by a qualitative utility function on the set of final states.

Mots clés: Qualitative approaches

Domaines: Intelligence artificielle [cs.AI]

Régis Sabbadin, Hélène Fargier, Jérôme Lang. Towards qualitative approaches to multi-stage decision making. International Journal of Approximate Reasoning, 1998, 19 (3-4), pp.441-471. ⟨10.1016/S0888-613X(98)10019-1⟩. ⟨hal-02695199⟩