Results 221 to 230 of about 608,869 (263)

Probabilistic Inference and Influence Diagrams

Operations Research, 1988
An influence diagram is a network representation for probabilistic and decision analysis models. The nodes correspond to variables which can be constants, uncertain quantities, decisions, or objectives. The arcs reveal the probabilistic dependence of the uncertain quantities and the information available at the time of the decisions. The detailed data
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Interactive dynamic influence diagrams

Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, 2007
Partially Observable Markov Decision Processes (POMDPs) emerged as the primary framework for decision-theoretic planning in single agent settings. Solutions to POMDPs are optimal plans which are conditional on future observations. Dynamic Influence Diagrams (DIDs) are computational representations of POMDPs which compute solutions for finite time ...
Kyle Polich, Piotr J. Gmytrasiewicz
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Comment on Influence Diagram Retrospective

Decision Analysis, 2006
Influence diagrams were first used in 1973 as a way to model political conflicts in the Persian Gulf and measure the value of information collected by the Defense Intelligence Agency. The number of scenarios for events in the region was too large to be represented as a conventional decision tree model.
Ronald A. Howard, James E. Matheson, Miley W. (Lee) Merkhofer, Allen C. Miller, D. Warner North   +4 more
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Dynamic programming and influence diagrams

IEEE Transactions on Systems, Man, and Cybernetics, 1990
The concept of a super value node is developed to extend the theory of influence diagrams to allow dynamic programming to be performed within this graphical modeling framework. The operations necessary to exploit the presence of these nodes and efficiently analyze the models are developed.
Joseph A. Tatman, Ross D. Shachter
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The Influence of Influence Diagrams on Artificial Intelligence

Decision Analysis, 2005
Howard and Matheson’s article “Influence Diagrams” has had a substantial impact on research in artificial intelligence (AI). In this perspective, I briefly discuss the importance of influence diagrams as a model for decision making under uncertainty in the AI research community; but I also identify some of the less direct, but no less important ...
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Sensitivity analysis in influence diagrams

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2003
The influence diagram framework serves as a powerful modeling tool for symmetric decision problems with a single decision maker. However, one of the main difficulties when representing decision problems using influence diagrams is eliciting the utilities and the probabilities.
Thomas D. Nielsen, Finn Verner Jensen
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On SPI for Evaluating Influence Diagrams

2014
An Influence Diagram is a probabilistic graphical model used to represent and solve decision problems under uncertainty. Its evaluation requires to perform a series of combinations and marginalizations with the potentials attached to the Influence Diagram.
Rafael Cabañas 0001, Anders L. Madsen, Andrés Cano, Manuel Gómez-Olmedo   +3 more
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Supporting Negotiations over Influence Diagrams

Decision Analysis, 2009
We deal with issues concerning negotiation support for group decisions over influence diagrams, when the group members disagree about utility and probability assessments. We base our discussion on a modification of the balanced increment solution, which guarantees a final negotiated Pareto optimal alternative.
Jesus Rios, David Ríos Insua
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Extended Influence Diagram Generation

2007
One step towards achieving high interoperability is to get an understanding of the current degree of interoperability, which calls for interoperability analyses. Extended influence diagrams have been proposed as an approach for conducting such interoperability analyses [1].
Robert Lagerström, Pontus Johnson, Per Närman   +2 more
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An ordered examination of influence diagrams

Networks, 1990
AbstractInfluence diagrams are a directed network representation for decision making under uncertainty. The nodes in the diagram represent uncertain and decision variables, and the arcs indicate probabilistic dependence and observability. This paper examines the graphical orderings underlying the influence diagram and the primitive interchange ...
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