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Decision-making involving low probability high consequence events under risk and uncertainty

  • Air Force Research Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Research in progress described in this paper addresses the problem of decision making in situations involving low probability high consequence events. The traditional Expected Utility Model (EU) has significant limitations in such circumstances as documented in multiple research results. The models discussed in this paper is an adaptation of the Multiple Quantile Model (MQT) representing a rational decision support scheme suited to regular as well as low probability high consequence events to the complex dynamic scenarios, in which decision making has to be based on highly uncertain, often unreliable heterogeneous data and information. The core of this scheme is a combination of the Multiple Quantile Theory with the Transferable Belief Model (TBM) and Anytime Decision making. An example of this approach with numeric simulations is given and the directions of future work are outlined.

Original languageEnglish
Title of host publication2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509063802
DOIs
StatePublished - May 16 2017
Event2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2017 - Savannah, United States
Duration: Mar 27 2017Mar 31 2017

Publication series

Name2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2017

Conference

Conference2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2017
Country/TerritoryUnited States
CitySavannah
Period03/27/1703/31/17

Keywords

  • Cumulative Prospect Theory
  • Decision Theory
  • Dempster-Shafer Theory
  • Multiple Quantile Theory
  • Situation Assessment
  • Transferrable Belief Model

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