Abstract. An influence diagram is a dual graphical and numerical rep-resentation of a decision problem under uncertainty. An influence dia-gram model that simultaneously incorporates discrete and continuous chance variables is utilized to consider both active and passive signals into the decision-making process to determine the optimal action to take against a potential threat. The proposed model incorporates non-Gaussian continuous chance variables using an approximation with mix-tures of truncated exponentials functions. An example requiring an air-craft to use observations of an IFF transponder and a radar pulse repeti-tion signal to determine whether or not to fire upon a target is presented.
Abstract. Influence diagrams are probabilistic graphical models used to represent and solve decision...
There are three phases in the life of a decision problem, specification, solution, and rep-resentati...
AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex ...
An influence diagram is a network representation of probabilistic inference and decision analysis mo...
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for represe...
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for represe...
While decision trees are a popular formal and quantitative method for determining an optimal decisio...
This mathematics in industry project explores influence diagrams as tools for decision making. Multi...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
This paper proposes a new decision making approch based on quantitative possibilistic influence diag...
Influence diagrams (IDs) are one of the most commonly used graphical decision models for reasoning u...
This is a short 9-pp version of a longer un-published working paper titled "Decision Making with Hyb...
We simulate and analyze pilot decision making in one-on-one air combat using an influence diagram. U...
Presented at International Conference on Emergency Preparedness "The Challenges of Mass Evacuation" ...
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert sy...
Abstract. Influence diagrams are probabilistic graphical models used to represent and solve decision...
There are three phases in the life of a decision problem, specification, solution, and rep-resentati...
AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex ...
An influence diagram is a network representation of probabilistic inference and decision analysis mo...
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for represe...
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for represe...
While decision trees are a popular formal and quantitative method for determining an optimal decisio...
This mathematics in industry project explores influence diagrams as tools for decision making. Multi...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
This paper proposes a new decision making approch based on quantitative possibilistic influence diag...
Influence diagrams (IDs) are one of the most commonly used graphical decision models for reasoning u...
This is a short 9-pp version of a longer un-published working paper titled "Decision Making with Hyb...
We simulate and analyze pilot decision making in one-on-one air combat using an influence diagram. U...
Presented at International Conference on Emergency Preparedness "The Challenges of Mass Evacuation" ...
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert sy...
Abstract. Influence diagrams are probabilistic graphical models used to represent and solve decision...
There are three phases in the life of a decision problem, specification, solution, and rep-resentati...
AbstractInfluence diagrams have been used effectively in applied decision analysis to model complex ...