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Multi‐agent distributed intelligent system based on fuzzy decision making
Author(s) -
Fazlollahi Bijan,
Vahidov Rustam M.,
Aliev Rafik A.
Publication year - 2000
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 - 10.1002/1098-111x(200009)15:9<849::aid-int2>3.0.co;2-i
Subject(s) - computer science , fuzzy logic , artificial intelligence , intelligent decision support system , neuro fuzzy , set (abstract data type) , intelligent agent , decision support system , knowledge base , base (topology) , fuzzy rule , computational intelligence , fuzzy set , data mining , fuzzy control system , mathematics , mathematical analysis , programming language
Generally decision making for solving ill‐structured problems in DSS takes place in uncertain situations. The main drawbacks of existing traditional DSS are inefficiencies associated with dealing with complex models and large databases. Usually a fuzzy DSS has many input variables and, hence, its knowledge base, containing the totality of fuzzy rules, is very large. Large rule base leads to disadvantages in speed, reliability, and complexity of DSS. This paper introduces an alternative concept for designing fuzzy DSS based on multi‐agent distributed artificial intelligent technology and fuzzy decision making. The main idea of the proposed DSS is based on granulation of the overall system intelligence between cooperative autonomous intelligent agents capable of competing and cooperating with each other in order to propose a total solution to the problem and organization (combining individual solutions) of the proposed solution into the final solution. It is supposed that every agent in DSS is characterized by a set of fuzzy criteria of unequal importance and definition of a “winner” agent is based on multi‐criteria fuzzy decision making involving unequal objectives. © 2000 John Wiley & Sons, Inc.