Design of inexact reasoning systems for management problem diagnosis

Date

1990-05

Journal Title

Journal ISSN

Volume Title

Publisher

Texas Tech University

Abstract

Human decision-making becomes more complicated when decision problems arise in less-than-perfect situations-- situations with information imperfection. In these situations, decision quality degrades severely because of the limitation of a human's reasoning capabilities.

Promoted by advances in modern computing technology, intelligent decision aid systems have surfaced as a solution to solve that problem. The core of such decision aid systems is an inexact reasoning system.

The purpose of this research was to design a robust and efficient reasoning system that can handle the problems with information imperfection effectively. The problem domain of focus was managerial problem diagnosis at a strategic decision level. The research question was whether the new inexact reasoning architecture can help managers to diagnose their problems in a more robust and efficient way than existing inexact reasoning architectures.

The task of designing a robust and efficient inexact reasoning architecture was performed by synthesizing the knowledge in two major fields of modern computing technology: the representation of imperfect knowledge and information, and the connectionist computational architectures.

Design of the inexact reasoning system, named as GIROS, involved: i) formulation of design criteria; ii) conceptualization and functional specification; iii) architectural design; iv) detailed design; and v) coding and verification. Detailed design required designing a series of algorithms for the functional specification of GIROS.

To accomplish the research purpose and to answer the research question, prototype system development was adopted as a base for the methodology of the research. A checklist of the functional capabilities of inexact reasoning systems was developed as a framework for the comparative evaluation of CIROS and the selected inexact reasoning systems. Then, a comparative evaluation was done based on the framework.

The evaluation and a demonstration of the use of CIROS seemed sufficient to conclude that GIROS is a robust and efficient inexact reasoning architecture. Moreover, CIROS can handle more diverse types of information imperfection than the selected inexact reasoning systems. CIROS can perform inexact inferencing more efficiently than many other inexact reasoning architectures. And GIROS has its own justification/explanation facility, a capability that is nonexistent in the connectionist architectures.

Description

Keywords

Decision making -- Mathematical models, Management -- Simulation methods, Expert systems (Computer science), Reasoning, Problem solving

Citation