The aim of this paper is the applying, in a particular case of human resources training and development, of some mathematical models of decision making under conditions of uncertainty. The models are also known in other applications, from other fields. In this article, we wanted to show that they can be also applied in human resources training and development, which represents an original contribution in this field. In uncertainty situations, the decisionmaker can not evaluate the apparition probability of the different stages of nature, since he does not have enough information and the variables are partially controllable. In such situations, the decision-maker can resort, for choosing the decisional variants, to different models (rules, t...
Dynamic decision-making under uncertainty has a long and distinguished history in opera-tions resear...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
Abstract. Maximum likelihood estimation (MLE) and heuristic predictive estimation (HPE) are two wide...
International audienceThe goal of this chapter is to provide a general introduction to decision maki...
Title: Decision under uncertainty - Investment in a human resource Authors: Emil Numminen & Fred...
Abstract. Decision Making is certainly the most important task of a manager and it is often a very d...
This thesis is focused on decision models for decision making under risk and uncertainty. The thesis...
The object of the research is the formalized problem of decision-making under conditions of complete...
The notions of risk and uncertainty are the subject of countless studies and specialized papers, bei...
The decision making (DM) problem is of great practical value in many areas of human activities. Most...
In the settings of decision-making-under-uncertainty problems, an agent takes an action on the envir...
Abstract—Mathematical programming plays a pivotal role in finding the solution for optimization prob...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
The volume delivers a wealth of effective methods to deal with various types of uncertainty inherent...
Uncertainty is a pervasive feature of many models in a variety of fields, from computer science to e...
Dynamic decision-making under uncertainty has a long and distinguished history in opera-tions resear...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
Abstract. Maximum likelihood estimation (MLE) and heuristic predictive estimation (HPE) are two wide...
International audienceThe goal of this chapter is to provide a general introduction to decision maki...
Title: Decision under uncertainty - Investment in a human resource Authors: Emil Numminen & Fred...
Abstract. Decision Making is certainly the most important task of a manager and it is often a very d...
This thesis is focused on decision models for decision making under risk and uncertainty. The thesis...
The object of the research is the formalized problem of decision-making under conditions of complete...
The notions of risk and uncertainty are the subject of countless studies and specialized papers, bei...
The decision making (DM) problem is of great practical value in many areas of human activities. Most...
In the settings of decision-making-under-uncertainty problems, an agent takes an action on the envir...
Abstract—Mathematical programming plays a pivotal role in finding the solution for optimization prob...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
The volume delivers a wealth of effective methods to deal with various types of uncertainty inherent...
Uncertainty is a pervasive feature of many models in a variety of fields, from computer science to e...
Dynamic decision-making under uncertainty has a long and distinguished history in opera-tions resear...
In this note, we stress the relevance of developing tools for modelling uncertainty in information m...
Abstract. Maximum likelihood estimation (MLE) and heuristic predictive estimation (HPE) are two wide...