A model for linguistic partial information in decision‐making problems | Zendy

Delgado M. | Zendy; Verdegay J. L. | Zendy; Vila M. A. | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

A model for linguistic partial information in decision‐making problems

Author(s) -

Delgado M.,

Verdegay J. L.,

Vila M. A.

Publication year - 1994

Publication title -

international journal of intelligent systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.291

H-Index - 87

eISSN - 1098-111X

pISSN - 0884-8173

DOI - 10.1002/int.4550090403

Subject(s) - computer science , term (time) , set (abstract data type) , interpretation (philosophy) , complete information , decision tree , artificial intelligence , decision maker , data mining , natural language processing , mathematics , operations research , mathematical economics , physics , quantum mechanics , programming language

A model is proposed for dealing with decision‐making problems in which the decision maker has a vague (linguistically assessed) and incomplete information about results and external factors (a quite usual situation in real decision cases). It is assumed here that utilities are evaluated in a term set of labels and the incomplete information is supposed to be a partial linguistic assignment of probability with values on a term set of linguistic likelihoods. the first step is to discuss a well‐fitted interpretation of that model. After that, basic decision rules based on fuzzy risk intervals are developed. Additionally the suitability of considering a hierarchical structure (represented by a tree) for the set of utility labels is analyzed. © 1994 John Wiley & Sons, Inc.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research