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Study on the adhesion performance of basalt fiber and polypropylene fiber based on unified phase-field theory and cohesive zone model. [PDF]

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Wen Z, Simeng W, Huiming W, Guanghui C.
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Influence Diagram Retrospective

Decision Analysis, 2005
Since the invention of Influence diagrams in the mid-1970s, they have become a ubiquitous tool for representing uncertain situations. This single diagram replaced awkward manipulations of decision trees and nature’s trees with a single representation that displays both the sequential and informational structure of decisions.
Ronald A. Howard, James E. Matheson
exaly   +2 more sources

The Influence of Influence Diagrams in Medicine

Decision Analysis, 2005
Although influence diagrams have used medical examples almost from their inception, that graphical representation of decision problems has disseminated surprisingly slowly in the medical literature and among clinicians performing decision analyses. Clinicians appear to prefer decision trees as their primary modeling metaphor. This perspective examines
Stephen G. Pauker, John B. Wong
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Reusable influence diagrams

Artificial Intelligence in Medicine, 1994
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert systems. Nevertheless, the most part of applications consists in stand-alone systems, concerning a very limited domain. On the other hand, Artificial Intelligence research has outlined Blackboard Architectures as the basis for building expert systems in ...
Riccardo Bellazzi, Silvana Quaglini
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Compiling influence diagrams

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 1996
This paper examines a class of algorithms for "compiling" influence diagrams into a set of simple decision rules. These decision rules define simple-to-execute, complete, consistent, and near-optimal decision procedures. These compilation algorithms can be used to derive decision procedures for manually solving time constrained decision problems.
Paul E. Lehner, Azar Sadigh
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Decomposition of influence diagrams

Journal of Applied Non-Classical Logics, 2001
When solving a decision problem we want to determine an optimal policy for the decision variables of interest. A policy for a decision variable is in principle a function over its past. However, some of the past may be irrelevant and for both communicational as well as computational reasons it is important not to deal with redundant variables in the ...
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Evaluating Influence Diagrams

Operations Research, 1986
An influence diagram is a graphical structure for modeling uncertain variables and decisions and explicitly revealing probabilistic dependence and the flow of information. It is an intuitive framework in which to formulate problems as perceived by decision makers and to incorporate the knowledge of experts.
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Mixed Influence Diagrams

2003
This paper presents an architecture for exact evaluation of influence diagrams containing a mixture of continuous and discrete variables. The proposed architecture is the first architecture for efficient exact solution of linear-quadratic conditional Gaussian influence diagrams with an additively decomposing utility function.
Anders L. Madsen, Frank Jensen
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Decomposable Probabilistic Influence Diagrams

Probability in the Engineering and Informational Sciences, 1991
Probabilistic influence diagrams are a useful stochastic modeling tool. To calculate probabilities of interest relative to a probabilistic influence diagram efficiently, it will be helpful for us to use an associated decomposable-directed graph. We first explore and discuss some graph-theoretic and conditional independence properties of decomposable ...
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