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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.