A GENERALIZED INTELLIGENT PROBLEM SOLVING SYSTEM BASED ON A RELATIONAL MODEL FOR KNOWLEDGE REPRESENTATION (SUPPORT SYSTEMS, EXPERT, DECISION AIDS).

Persistent Link:
http://hdl.handle.net/10150/183779
Title:
A GENERALIZED INTELLIGENT PROBLEM SOLVING SYSTEM BASED ON A RELATIONAL MODEL FOR KNOWLEDGE REPRESENTATION (SUPPORT SYSTEMS, EXPERT, DECISION AIDS).
Author:
PARK, SEUNG YIL.
Issue Date:
1986
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:
Over the past decade, two types of decision aids, i.e., decision support systems (DSS) and expert systems (ES), have been developed along parallel paths, showing some significant differences in their software architectures, capabilities, limitations, and other characteristics. The synergy of DSS and ES, however, has great potential for helping make possible a generalized approach to developing a decision aid that is powerful, intelligent, and friendly. This research establishes a framework for such decision aids in order to determine the elementary components and their interactions. Based on this framework, a generalized intelligent problem solving system (GIPSS) is deveolped as a decision aid generator. A relational model is designed to provide a unified logical view of each type of knowledge including factual data, modeling knowledge, and heuristic rules. In this knowledge model, a currently existing relational DBMS, with some extension, is utilized to manage each type of knowledge. For this purpose a relational resolution inference mechanism has been devised. A prototype GIPSS has been developed based on this framework. Two domain specific decision aids, COCOMO which estimates software development effort and cost, and CAPO which finds optimal process organization, have been implemented by using the GIPSS as a decision aid generator, demonstrating such features as its dynamic modeling capabilities and learning capabilities.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Decision making -- Computer programs.; Management -- Computer programs.; Expert systems (Computer science)
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Management Information Systems; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Nunamaker, Jay F.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleA GENERALIZED INTELLIGENT PROBLEM SOLVING SYSTEM BASED ON A RELATIONAL MODEL FOR KNOWLEDGE REPRESENTATION (SUPPORT SYSTEMS, EXPERT, DECISION AIDS).en_US
dc.creatorPARK, SEUNG YIL.en_US
dc.contributor.authorPARK, SEUNG YIL.en_US
dc.date.issued1986en_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.abstractOver the past decade, two types of decision aids, i.e., decision support systems (DSS) and expert systems (ES), have been developed along parallel paths, showing some significant differences in their software architectures, capabilities, limitations, and other characteristics. The synergy of DSS and ES, however, has great potential for helping make possible a generalized approach to developing a decision aid that is powerful, intelligent, and friendly. This research establishes a framework for such decision aids in order to determine the elementary components and their interactions. Based on this framework, a generalized intelligent problem solving system (GIPSS) is deveolped as a decision aid generator. A relational model is designed to provide a unified logical view of each type of knowledge including factual data, modeling knowledge, and heuristic rules. In this knowledge model, a currently existing relational DBMS, with some extension, is utilized to manage each type of knowledge. For this purpose a relational resolution inference mechanism has been devised. A prototype GIPSS has been developed based on this framework. Two domain specific decision aids, COCOMO which estimates software development effort and cost, and CAPO which finds optimal process organization, have been implemented by using the GIPSS as a decision aid generator, demonstrating such features as its dynamic modeling capabilities and learning capabilities.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDecision making -- Computer programs.en_US
dc.subjectManagement -- Computer programs.en_US
dc.subjectExpert systems (Computer science)en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineManagement Information Systemsen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorNunamaker, Jay F.en_US
dc.contributor.committeememberKonsynski, Bennen_US
dc.contributor.committeememberMarsten, Royen_US
dc.contributor.committeememberRaw, Averillen_US
dc.contributor.committeememberGreenfield, Arnieen_US
dc.identifier.proquest8613829en_US
dc.identifier.oclc697300478en_US
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