DocumentCode :
2458608
Title :
General approaches to the modelling of soft estimates and beliefs in strategic decision engineering
Author :
Tarassov, Valery B.
Author_Institution :
Bauman Moscow State Tech. Univ., Russia
fYear :
2002
fDate :
2002
Firstpage :
45
Lastpage :
49
Abstract :
Strategic decision engineering problems are formulated. To differ from conventional decision-making approaches, decision engineering faces ill-defined situations typical for strategic management. Here the modeling of various non-factors proper to decider\´s estimates, judgments and beliefs is of primary concern. The author introduces the concept of "soft estimates" to define flexible expert estimates taking into account non-factors classes which arise in decider\´s knowledge representation on bipolar scales. His main purpose in this paper is to specify a general mathematical framework for soft estimates and uncertain beliefs typical for strategic decision engineering. A logical-algebraic description of soft estimation approaches is given. Different types of bipolar scales are considered. Appropriate multi-valued and fuzzy logics are presented. Some early logical approaches to non-factors modeling are discussed A quasi-ordering relation induced by a class of negations is taken as a basis for representing judgments and beliefs on bipolar scales. An estimation algebra on bipolar scales is constructed. Some indices of estimate softness are suggested. Generalized fuzzy sets to model flexible linguistic estimates on bipolar scales are proposed.
Keywords :
artificial intelligence; belief maintenance; decision making; fuzzy logic; fuzzy set theory; knowledge representation; multivalued logic; Kleene algebra; bipolar scales; fuzzy logic; fuzzy set theory; knowledge representation; multivalued logic; negation; nonfactor modeling; soft estimation; strategic decision engineering; strategic management; Algebra; Artificial intelligence; Decision making; Decision theory; Engineering management; Fuzzy logic; Fuzzy sets; Humans; Knowledge engineering; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence Systems, 2002. (ICAIS 2002). 2002 IEEE International Conference on
Print_ISBN :
0-7695-1733-1
Type :
conf
DOI :
10.1109/ICAIS.2002.1048050
Filename :
1048050
Link To Document :
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