Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6854253 | Engineering Applications of Artificial Intelligence | 2018 | 8 Pages |
Abstract
We discuss the role that the Choquet integral plays in the aggregation of criteria satisfaction in multi-criteria decision functions. We show how the choice of the associated measure allows for the formulation of many types of multi-criteria decision functions. We note that the need for an ordering of the criteria satisfactions causes difficulties in situations in which there exists a probabilistic type of uncertainty in the knowledge of the criteria satisfactions. We discuss an approach, called the probabilistic exceedance method, for allowing the aggregation of probabilistically satisfied criteria.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ronald R. Yager, Naif Alajlan,