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Risk of Extreme Events in Multiobjective Decision Trees Part 2. Rare Events
Author(s) -
Frohwein Hendrik I.,
Haimes Yacov Y.,
Lambert James H.
Publication year - 2000
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/0272-4332.00012
Subject(s) - expected value , outcome (game theory) , conditional probability , decision tree , extreme value theory , expected utility hypothesis , conditional expectation , mathematics , statistics , value (mathematics) , random variable , mathematical optimization , econometrics , computer science , data mining , mathematical economics
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 second of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming that a random variable is observed only in the upper 100 (1 −α) percent of potential outcomes, where α is a cumulative probability 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 in part on approximating the conditional expected value by using statistics of extremes. An existing convenient approximation of the conditional expected value is shown to be separable into two constituent elements of risk and can thus be optimized, along with other objectives including the unconditional expected value of the outcome, in a multiobjective decision tree. An example of sequential decision making for remediation or environmental contamination is provided. The importance of the results for risk analyis beyond the minimization of conditional expected values is pointed out.