A Special Issue of International Journal of Approximate Reasoning on Decision Making under uncertainty and imprecision
摘要截稿:
全文截稿: 2018-11-30
影响因子: 2.678
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 计算机科学 - 3区
• 小类 : 计算机:人工智能 - 3区
Overview
The choice between several alternatives in a decision-making problem can be rendered difficult by the existence of uncertainty in the consequences of these alternatives. The standard approach to this issue is to model this alternative by means of probability theory, and to consider then a stochastic order, such as expected utility or stochastic dominance.
However, when the probabilistic information available is vague or scarce, the elicitation of a precise probability model can be difficult, and its use, questionable. In that case, it is possible to make use of tools from Imprecise Probability Theory, such as fuzzy measures, belief functions, possibility measures or lower/upper previsions, to model our uncertainty. Moreover, in some cases the incomplete information about the consequences of the alternatives can be tackled by means of the Theory of Fuzzy Sets.
This Special Issue aims at gathering significant advances in decision making problems with partial information. We encourage both theoretical and practically oriented papers. High-quality papers introducing novel approaches, improved methods or outstanding applications are welcome.
Topics of interest include, (but are not limited to):
- Decision making with imprecise probabilities.
- Connections between game theory, fuzzy measures and imprecise probabilities.
- Stochastic orderings with imprecise information.
- Multivariate modelling with imprecise probabilities.