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Modeling Risk in Sequential Decision Making with Interval Probabilities

  • Kurt J. Engemann
  • Holmes E. Miller
  • Ronald R. Yager
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 76)

Abstract

There are some drawbacks in attempting to apply the classical approach to risk analysis. We propose a new method to analyze scenarios involving a sequence of decisions which have imprecise information regarding event likelihoods. The decision maker’s knowledge and degree of optimism are included as key elements in the analysis. An example in risk management in presented.

Keywords

Decision Maker Interval Probability Minor Fire Cold Site Relationship Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1].
    Miller, H. and Engemann, K., “A Methodology for Managing Information-based Risk,” Information Resources Management Journal, 9: 2; 17–24, 1996.Google Scholar
  2. [2].
    Yager, R. and Kreinovich, V., “Decision Making Under Interval Probabilities,” International Journal of Approximate Reasoning, 22, 195–215, 1999.CrossRefGoogle Scholar
  3. [3].
    Engemann, K., and Yager, R., “On a General Approach to Decision Making Using Interval Probabilities,” Technical Report #MII-1950, Machine Intelligence Institute, Iona College, New Rochelle, NY, 1999.Google Scholar
  4. [4].
    O’Hagan, M., “Using Maximum Entropy-ordered Weighted Averaging to Construct a Fuzzy Neuron,” Proceedings of the 24th Annual IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 618–623, 1990.Google Scholar

Copyright information

© Physica-Verlag Heidelberg 2001

Authors and Affiliations

  • Kurt J. Engemann
    • 1
  • Holmes E. Miller
    • 2
  • Ronald R. Yager
    • 1
  1. 1.Iona CollegeNew RochelleUSA
  2. 2.Muhlenberg CollegeAllentownUSA

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