AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex systems, identify probabilistic dependence and characterize the flow of information. Their graphical representation and intuitive framework are particularly effective in representing knowledge from experts with diverse backgrounds and varying degrees of technical proficiency. They allow both a symbolic representation of the system interrelationships and a quantitative measure that can be of discrete or continuous functional form. By exploiting this abstraction hierarchy, successive degrees of specification can be made by several individuals, each encoding his or her expert knowledge of the problem and bounds on critical parameters. It is prop...
International audienceIn this paper, we focus on multi-criteria decision-making problems. We propose...
AbstractDespite their different perspectives, artificial intelligence (AI) and the disciplines of de...
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of ...
AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex ...
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert sy...
This mathematics in industry project explores influence diagrams as tools for decision making. Multi...
An influence diagram is a compact representation emphasizing the qualitative features of decision pr...
This thesis addresses some drawbacks related to the evaluation of influence diagrams (ID), which is ...
O presente trabalho discute a necessidade da representação e manipulação de incertezas na resolução ...
The usefulness of graphical models in reasoning and decision making stems from facilitating four mai...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
In an earlier paper, a general approach to prescribing decision procedures for a command and control...
Influence Diagrams (IDs) are one of the most commonly used graphical and mathematical decision mode...
This paper describes GAMEES (Graphical Modelling Environment for Expert Systems), an interactive gra...
In this paper, we develop a qualitative theory of influence diagrams that can be used to model and s...
International audienceIn this paper, we focus on multi-criteria decision-making problems. We propose...
AbstractDespite their different perspectives, artificial intelligence (AI) and the disciplines of de...
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of ...
AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex ...
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert sy...
This mathematics in industry project explores influence diagrams as tools for decision making. Multi...
An influence diagram is a compact representation emphasizing the qualitative features of decision pr...
This thesis addresses some drawbacks related to the evaluation of influence diagrams (ID), which is ...
O presente trabalho discute a necessidade da representação e manipulação de incertezas na resolução ...
The usefulness of graphical models in reasoning and decision making stems from facilitating four mai...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
In an earlier paper, a general approach to prescribing decision procedures for a command and control...
Influence Diagrams (IDs) are one of the most commonly used graphical and mathematical decision mode...
This paper describes GAMEES (Graphical Modelling Environment for Expert Systems), an interactive gra...
In this paper, we develop a qualitative theory of influence diagrams that can be used to model and s...
International audienceIn this paper, we focus on multi-criteria decision-making problems. We propose...
AbstractDespite their different perspectives, artificial intelligence (AI) and the disciplines of de...
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of ...