Qualitative decision rules under uncertainty

Didier Dubois (1, 2) , Hélène Fargier (1, 2)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 CNRS - Centre National de la Recherche Scientifique

This paper is a survey of qualitative decision theory focusing on available decision rules under uncertainty, and their properties. It is pointed out that two main approaches exist according to whether degrees of uncertainty and degrees of utility are commensurate (that is, belong to a unique scale) or not. Savage-like axiom systems for both approaches are surveyed. In such a framework, acts are functions from states to results, and decision rules are derived from first principles, bearing on a preference relation on acts. It is shown that the emerging uncertainty theory in qualitative settings is possibility theory rather than probability theory. However these approaches lead to criteria that are either little decisive due to incomparability, or too adventurous because focusing on the most plausible states, or yet lacking discrimination because or the coarseness of the value scale. Some suggestions to overcome these defects are pointed out.

Domaines: Intelligence artificielle [cs.AI]

Didier Dubois, Hélène Fargier. Qualitative decision rules under uncertainty. Giacomo Della Riccia; Didier Dubois; Rudolf Kruse; Hans-J. Lenz. Planning Based on Decision Theory, 472, Springer Wien, pp.3-26, 2003, International Centre for Mechanical Sciences book series (CISM), 978-3-211-40756-1. ⟨10.1007/978-3-7091-2530-4_1⟩. ⟨hal-03463119⟩