Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well‐known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Risk Analysis Wiley

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Risk Analysis, Volume 20 (1) – Feb 1, 2000

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Publisher
Wiley
Copyright
Copyright © 2000 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0272-4332
eISSN
1539-6924
DOI
10.1111/0272-4332.00011
Publisher site
See Article on Publisher Site

Abstract

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well‐known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given.

Journal

Risk AnalysisWiley

Published: Feb 1, 2000

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