AN EXPERT SYSTEM USING FUZZY SET REPRESENTATIONS FOR RULES AND VALUES TO MAKE MANAGEMENT DECISIONS IN A BUSINESS GAME.

Persistent Link:
http://hdl.handle.net/10150/187643
Title:
AN EXPERT SYSTEM USING FUZZY SET REPRESENTATIONS FOR RULES AND VALUES TO MAKE MANAGEMENT DECISIONS IN A BUSINESS GAME.
Author:
DICKINSON, DEAN BERKELEY.
Issue Date:
1984
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation reports on an effort to design, construct, test, and adjust an expert system for making certain business decisions. A widely used approach to recurring judgmental decisions in business and other social organizations is the "rule-based decision system". This arrangement employs staff experts to propose decision choices and selections to a decisionmaker. Such decisions can be very important because of the large resources involved. Rules and values encountered in such systems are often vague and uncertain. Major questions explored by this experimental effort were: (1) could the output of such a decision system be mimicked easily by a mechanism incorporating the rules people say they use, and (2) could the imprecision endemic in such a system be represented by fuzzy set constructs. The task environment chosen for the effort was a computer-based game which required player teams to make a number of interrelated, recurring decisions in a realistic business situation. The primary purpose of this research is to determine the feasibility of using these methods in real decision systems. The expert system which resulted is a relatively complicated, feed-forward network of "simple" inferences, each with no more than one consequent and one or two antecedents. Rules elicited from an expert in the game or from published game instructions become the causal implications in these inferences. Fuzzy relations are used to represent imprecise rules and two distinctly different fuzzy set formats are employed to represent imprecise values. Once imprecision appears from the environment or rules the mechanism propagates it coherently through the inference network to the proposed decision values. The mechanism performs as well as the average human team, even though the strategy is relatively simple and the inferences crude linear approximations. Key aspects of this model, distinct from previous work, include: (1) the use of a mechanism to propose decisions in situations usually considered ill-structured; (2) the use of continuous rather than two-valued variables and functions; (3) the large scale employment of fuzzy set constructs to represent imprecision; and (4) use of feed forward network structure and simple inferences to propose human-like decisions.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Decision making -- Data processing.; Decision making -- Simulation methods.; Computer simulation.; Expert systems (Computer science); Management -- Data processing.; Management -- Simulation methods.; Management games -- Data processing.; Management science -- Data processing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Systems and Industrial Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Ferrell, William R.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleAN EXPERT SYSTEM USING FUZZY SET REPRESENTATIONS FOR RULES AND VALUES TO MAKE MANAGEMENT DECISIONS IN A BUSINESS GAME.en_US
dc.creatorDICKINSON, DEAN BERKELEY.en_US
dc.contributor.authorDICKINSON, DEAN BERKELEY.en_US
dc.date.issued1984en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation reports on an effort to design, construct, test, and adjust an expert system for making certain business decisions. A widely used approach to recurring judgmental decisions in business and other social organizations is the "rule-based decision system". This arrangement employs staff experts to propose decision choices and selections to a decisionmaker. Such decisions can be very important because of the large resources involved. Rules and values encountered in such systems are often vague and uncertain. Major questions explored by this experimental effort were: (1) could the output of such a decision system be mimicked easily by a mechanism incorporating the rules people say they use, and (2) could the imprecision endemic in such a system be represented by fuzzy set constructs. The task environment chosen for the effort was a computer-based game which required player teams to make a number of interrelated, recurring decisions in a realistic business situation. The primary purpose of this research is to determine the feasibility of using these methods in real decision systems. The expert system which resulted is a relatively complicated, feed-forward network of "simple" inferences, each with no more than one consequent and one or two antecedents. Rules elicited from an expert in the game or from published game instructions become the causal implications in these inferences. Fuzzy relations are used to represent imprecise rules and two distinctly different fuzzy set formats are employed to represent imprecise values. Once imprecision appears from the environment or rules the mechanism propagates it coherently through the inference network to the proposed decision values. The mechanism performs as well as the average human team, even though the strategy is relatively simple and the inferences crude linear approximations. Key aspects of this model, distinct from previous work, include: (1) the use of a mechanism to propose decisions in situations usually considered ill-structured; (2) the use of continuous rather than two-valued variables and functions; (3) the large scale employment of fuzzy set constructs to represent imprecision; and (4) use of feed forward network structure and simple inferences to propose human-like decisions.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDecision making -- Data processing.en_US
dc.subjectDecision making -- Simulation methods.en_US
dc.subjectComputer simulation.en_US
dc.subjectExpert systems (Computer science)en_US
dc.subjectManagement -- Data processing.en_US
dc.subjectManagement -- Simulation methods.en_US
dc.subjectManagement games -- Data processing.en_US
dc.subjectManagement science -- Data processing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSystems and Industrial Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorFerrell, William R.en_US
dc.identifier.proquest8412661en_US
dc.identifier.oclc690914722en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.