Modeling Indeterminacy in Decision Situations
We present theoretical foundations and computational procedures of a theory for analyzing decisions under risk, when the available information is vague and imprecise. The impreciseness is expressed by a set of global distributions T over a set of space S, where the latter represents the classes of all probability and utility measures over a set of discrete outcomes. We show how local distributions, i.e. distributions over projections of S on various subspaces of S, can be derived from T and introduce consistency measures expressing the extent into which user-asserted local distributions can be used for defining T. The evaluation model used is based on the expected utility, but this is not a necessary restriction. The approach allows a decision maker to be as deliberately imprecise as she feels natural, as well as provide her with the means for expressing varying degrees of imprecision in the input sentences.
|Date of creation:||Oct 1997|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.iiasa.ac.at/Publications/Catalog/PUB_ONLINE.htmlEmail:
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:wop:iasawp:ir97044. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.