Refined expected value decision rules

被引:2
作者
Yager, Ronald R. [1 ]
机构
[1] Iona Coll, Machine Intelligence Inst, New Rochelle, NY 10801 USA
关键词
Probabilistic uncertainty; Stochastic dominance; Expected value; Decision making;
D O I
10.1016/j.inffus.2017.10.008
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We consider the difficult problem of choosing between alternatives where the payoffs for the alternatives are uncertain and modeled via discrete probability distributions. One popular approach for making a choice in this complex environment is to use the idea of expected value; we prefer alternatives with larger expected value. Here we suggest an approach for refining the calculation of the expected value to allow for the inclusion of a requirement that we prefer an alternative with payoff probability distribution P1 to an alternative with payoff probability distribution P2 by assuring that expected value of P1 is larger then the expected value of P2.
引用
收藏
页码:174 / 178
页数:5
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