
An IntervalValued Utility Theory for Decision Making with DempsterShafer Belief Functions
The main goal of this paper is to describe an axiomatic utility theory f...
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Propagation of Belief Functions: A Distributed Approach
In this paper, we describe a scheme for propagating belief functions in ...
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Modifiable Combining Functions
Modifiable combining functions are a synthesis of two common approaches ...
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An Axiomatic Framework for Bayesian and Belieffunction Propagation
In this paper, we describe an abstract framework and axioms under which ...
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ValuationBased Systems for Discrete Optimization
This paper describes valuationbased systems for representing and solvin...
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A Fusion Algorithm for Solving Bayesian Decision Problems
This paper proposes a new method for solving Bayesian decision problems....
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Conditional Independence in Uncertainty Theories
This paper introduces the notions of independence and conditional indepe...
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Valuation Networks and Conditional Independence
Valuation networks have been proposed as graphical representations of va...
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A Comparison of LauritzenSpiegelhalter, Hugin, and ShenoyShafer Architectures for Computing Marginals of Probability Distributions
In the last decade, several architectures have been proposed for exact c...
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On Transformations between Probability and Spohnian Disbelief Functions
In this paper, we analyze the relationship between probability and Spohn...
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A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs
In this paper, we formulate a qualitative "linear" utility theory for lo...
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A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory
In this paper we analyze two recent axiomatic approaches proposed by Dub...
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Statistical Decisions Using Likelihood Information Without Prior Probabilities
This paper presents a decisiontheoretic approach to statistical inferen...
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A Linear Belief Function Approach to Portfolio Evaluation
By elaborating on the notion of linear belief functions (Dempster 1990; ...
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Decision Making with Partially Consonant Belief Functions
This paper studies decision making for Walley's partially consonant beli...
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Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative t...
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Hybrid Bayesian Networks with Linear Deterministic Variables
When a hybrid Bayesian network has conditionally deterministic variables...
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Solving Hybrid Influence Diagrams with Deterministic Variables
We describe a framework and an algorithm for solving hybrid influence di...
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Prakash P. Shenoy
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Ronald G. Harper Distinguished Professor of Artificial Intelligence and Director, Center for Business Analytics Research (CBAR)