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Some Extensions of Domain Criteria in Decision Making under Uncertainty *
Author(s) -
Eiselt Horst A.,
Langley Ann
Publication year - 1990
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1990.tb00321.x
Subject(s) - domain (mathematical analysis) , parametric statistics , computer science , value (mathematics) , computation , distribution (mathematics) , mathematical economics , management science , mathematical optimization , operations research , mathematics , economics , algorithm , machine learning , statistics , mathematical analysis
This paper examines some approaches to decision problems under uncertainty. Starr's [29] domain criterion is presented and modified to take into account different philosophies concerning the desirability of winning versus the importance of avoiding losses. The concept of expected value of distribution information is defined and its computation is illustrated with a numerical example. Target values are then introduced into the model and a parametric procedure is used to maximize the chances of achieving a certain level of the given objective. Finally, we show how the concepts developed in this paper might provide further insight into some decision situations reported in the literature.