NDLI: Influence Diagram Model with Interval-Valued Utilities

Content Provider	IEEE Xplore Digital Library
Author	Lihua Zhou Weiyi Liu Lizhen Wang
Copyright Year	2009
Abstract	Influence diagrams (IDs) are a popular framework representing a decision maker’s belief and preferences about a sequence of decisions to be made under uncertainty. The quantification of IDs which consists of defining conditional probabilities for chance nodes and utility functions for value nodes is not always obvious. In fact, decision makers cannot always provide exact utilities and in some cases, it is more convincible to describe utilities with interval values than precise ones. This paper is about extending general IDs (with precise single-valued parameters) into IDs with interval-valued utilities. Such extension is interesting because it enables one to model decision making processes in the situation that utilities are represented by interval values. This paper extend Gibbs sampling algorithm to the Bayesian network (BN) containing interval-valued probabilities for approximate inference and propose a method to evaluate IDs with interval-valued utilities based on the BN inference.
Starting Page	601
Ending Page	605
File Size	294159
Page Count	5
File Format	PDF
ISBN	9780769539294
e-ISBN	9781424454211
DOI	10.1109/DASC.2009.64
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Costs Decision making Interval-valued parameters Influence diagrams State-space methods Petroleum Bayesian methods Utility theory Intrusion detection Sampling methods Inference algorithms Bayesian network
Content Type	Text
Resource Type	Article

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