There exist techniques for decision making under specific types of uncertainty, such as probabilistic, fuzzy, etc. Each of the corresponding ways of describing uncertainty has its advantages and limitations. As a result, new techniques for describing uncertainty appear all the time. Instead of trying to extend the existing decision making idea to each of these new techniques one by one, we attempt to develop a general approach that would cover all possible uncertainty techniques
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
AbstractUncertainty is generally defined as ‘that which is not precisely known’. This definition per...
Uncertainty is very important in risk analysis. A natural way to describe this uncertainty is to des...
This study considers an expanded meaning of uncertainty as it affects decision-makers. The definit...
Different types of uncertainty are widely spread in all areas of human activity. Probabilistic uncer...
Different types of uncertainty are widely spread in all areas of human activity. Probabilistic uncer...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
International audienceThe goal of this chapter is to provide a general introduction to decision maki...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
We study decision problems in which consequences of the various alternative actions depend on states...
We study decision problems in which consequences of the various alternative actions depend on states...
Abstract. The historical range and current applications of important ideas about uncertainty are rev...
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
AbstractUncertainty is generally defined as ‘that which is not precisely known’. This definition per...
Uncertainty is very important in risk analysis. A natural way to describe this uncertainty is to des...
This study considers an expanded meaning of uncertainty as it affects decision-makers. The definit...
Different types of uncertainty are widely spread in all areas of human activity. Probabilistic uncer...
Different types of uncertainty are widely spread in all areas of human activity. Probabilistic uncer...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
International audienceThe goal of this chapter is to provide a general introduction to decision maki...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
We study decision problems in which consequences of the various alternative actions depend on states...
We study decision problems in which consequences of the various alternative actions depend on states...
Abstract. The historical range and current applications of important ideas about uncertainty are rev...
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
This paper introduces the likelihood method for decision under uncertainty. The method allows the qu...
AbstractUncertainty is generally defined as ‘that which is not precisely known’. This definition per...