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Databases in large AI systems
literature Expert systems
Knowledge acquisition
Knowledge engineering
Frieson, 0 and Gloshani, F 'Databases in large AI systems' A I Mag. Vol 10 No 4 (1989) pp 17-19
Gruber, T R 'Automated knowledge acquisition for strategic knowledge' Mach. Learn. Vol 4 Nos 3/4 (December 1989) pp 293-336
Blaekman, M J 'CASE for expert systems' A I Expert Vol 5 No 2 (February 1990) pp 26-31
Databases are at the heart of most real-world knowledge-based systems. The management and effective use of these databases will be the limiting factors in our ability to build ever more complex AI systems. This article reports on a workshop that explored how databases and their associated technologies can best be used in the development of large AI applications.
Keravnou, E T and Washbrook, J 'What is a deep expert system? An analysis of the architectural requirements of second-generation expert systems' Knowl. Eng. Rev. Vol 4 No 3 (1989) pp 205-233
This article presents a computer-mediated method for acquiring strategic knowledge. The general knowledge acquisition problem and the special difficulties of acquiring strategic knowledge are analysed in terms of representation mismatch: the difference between the form in which knowledge is available from the world and the form required for knowledge systems. ASK is an interactive knowledge acquisition tool that elicits strategic knowledge from people in the form of justification for action choices and generates strategy rules that operationalize and generalize the expert's advice. The basic approach is demonstrated with a human-computer dialogue in which ASK acquires strategic knowledge for medical diagnosis and treatment. The paper concludes by discussing the contribution of knowledge representation to automated knowledge acquisition.
The limitations of first-generation expert systems are analysed (under the categories human-computer interaction, problem solving flexibility, and extensibility), thus setting the design goals for the next generation of systems. On the basis of the proposed analysis, second-generation architectures are reviewed and compared, with a final conclusions section presenting requirements for a generic second-generation architecture.
Knowledge bases
Leung, KS, Wong, M H, and Lam, W 'A fuzzy expert database system' Data Knowl. Eng. Vol 4 No 4 (December 1989) pp 287-304
Bareiss, R, Porter, B W and Murray, K S 'Supporting start-to-finish development' Mach. Learn. Vol 4 Nos 3-4 (December 1989) pp 285-291
This paper presents a fuzzy expert database system which is an integration of a fuzzy expert system building tool called SYSTEM Z-II and a database management system called Rdb/%'MS. The system is able to extract fuzzy data and terms stored in a database and used in the fuzzy reasoning in an expert system. It can also retrieve information by fuzzy database queries which are generated by the expert system automatically. Many expert systems in different domain areas such as decision making can be constructed. Sample applications are described to demonstrate the flexibility and power of this system. The fuzzy query language defined and used in the system can also be used independently as a fuzzy enquiry tool in database applications.
Developing knowledge bases using knowledge-acquisition tools is difficult because each stage of development requires performing a distinct knowledgeacquisition task. This paper describes these different tasks and surveys current tools that perform them. It also addresses two issues confronting tools for start-to-finish development of knowledge bases. The first issue is how to support Protos, a knowledge acquisition tool that adjusts the training it expects and assistance it provides as its knowledge grows. The second issue is how to integrate new information into a large knowledge base. This issue is addressed in the description of a second tool, KI, that evaluates new information to determine its consequences for existing knowledge.
Vol 4 N o 2 June 1991
This article focuses on the use of information-engineering analysis techniques (data modelling), process modelling and joint application design) for expert systems development. To illustrate the usefulness of information engineering for expert systems, the author explores using joint application design as a framework for more effective knowledge acquisition. The technique requires a person trained in group facilitation, conflict management, concensus development, and an appropriate systems-development methodology.
Howard, H C 'KADBASE: interfacing expert systems with databases' IEEE Expert Vol 4 No 3 (1989) pp 65-76 A knowledge-aided database management system prototype called KADBASE is described. K A D B A S E is a flexible interface in which multiple databases and knowledge-aided database systems can communicate as independent, self-descriptive components within a loosely coupled distributed engineering computer system. The authors describe the final architecture of their working prototype, demonstrate its use in engineering applications, and provide examples from two civil engineering knowledge-based systems: SPEX, a structural component design system, and HICOST, a building-cost estimator.
Tomiyama, T and Ten Hagen, P J W 'Representing knowledge in two distinct descriptions: extensional versus intentional' Artif. Intell. Eng. Vol 5 No 1 (January 1990) pp 23-32 A theory of knowledge is described on which CAD systems can be based. Two distinct description methods--extensional and intensional--are presented and then compared in the context of CAD applications. It is shown that extensional description methods are more suitable for a future intelligent CAD system due to their data streams being frequently modified. Intensional description methods are found to be better in performing other tasks, such as simple queries. The paper ends by proposing a new data description method. 117
Knowledge acquisition
Knowledge engineering
Frieson, 0 and Gloshani, F 'Databases in large AI systems' A I Mag. Vol 10 No 4 (1989) pp 17-19
Gruber, T R 'Automated knowledge acquisition for strategic knowledge' Mach. Learn. Vol 4 Nos 3/4 (December 1989) pp 293-336
Blaekman, M J 'CASE for expert systems' A I Expert Vol 5 No 2 (February 1990) pp 26-31
Databases are at the heart of most real-world knowledge-based systems. The management and effective use of these databases will be the limiting factors in our ability to build ever more complex AI systems. This article reports on a workshop that explored how databases and their associated technologies can best be used in the development of large AI applications.
Keravnou, E T and Washbrook, J 'What is a deep expert system? An analysis of the architectural requirements of second-generation expert systems' Knowl. Eng. Rev. Vol 4 No 3 (1989) pp 205-233
This article presents a computer-mediated method for acquiring strategic knowledge. The general knowledge acquisition problem and the special difficulties of acquiring strategic knowledge are analysed in terms of representation mismatch: the difference between the form in which knowledge is available from the world and the form required for knowledge systems. ASK is an interactive knowledge acquisition tool that elicits strategic knowledge from people in the form of justification for action choices and generates strategy rules that operationalize and generalize the expert's advice. The basic approach is demonstrated with a human-computer dialogue in which ASK acquires strategic knowledge for medical diagnosis and treatment. The paper concludes by discussing the contribution of knowledge representation to automated knowledge acquisition.
The limitations of first-generation expert systems are analysed (under the categories human-computer interaction, problem solving flexibility, and extensibility), thus setting the design goals for the next generation of systems. On the basis of the proposed analysis, second-generation architectures are reviewed and compared, with a final conclusions section presenting requirements for a generic second-generation architecture.
Knowledge bases
Leung, KS, Wong, M H, and Lam, W 'A fuzzy expert database system' Data Knowl. Eng. Vol 4 No 4 (December 1989) pp 287-304
Bareiss, R, Porter, B W and Murray, K S 'Supporting start-to-finish development' Mach. Learn. Vol 4 Nos 3-4 (December 1989) pp 285-291
This paper presents a fuzzy expert database system which is an integration of a fuzzy expert system building tool called SYSTEM Z-II and a database management system called Rdb/%'MS. The system is able to extract fuzzy data and terms stored in a database and used in the fuzzy reasoning in an expert system. It can also retrieve information by fuzzy database queries which are generated by the expert system automatically. Many expert systems in different domain areas such as decision making can be constructed. Sample applications are described to demonstrate the flexibility and power of this system. The fuzzy query language defined and used in the system can also be used independently as a fuzzy enquiry tool in database applications.
Developing knowledge bases using knowledge-acquisition tools is difficult because each stage of development requires performing a distinct knowledgeacquisition task. This paper describes these different tasks and surveys current tools that perform them. It also addresses two issues confronting tools for start-to-finish development of knowledge bases. The first issue is how to support Protos, a knowledge acquisition tool that adjusts the training it expects and assistance it provides as its knowledge grows. The second issue is how to integrate new information into a large knowledge base. This issue is addressed in the description of a second tool, KI, that evaluates new information to determine its consequences for existing knowledge.
Vol 4 N o 2 June 1991
This article focuses on the use of information-engineering analysis techniques (data modelling), process modelling and joint application design) for expert systems development. To illustrate the usefulness of information engineering for expert systems, the author explores using joint application design as a framework for more effective knowledge acquisition. The technique requires a person trained in group facilitation, conflict management, concensus development, and an appropriate systems-development methodology.
Howard, H C 'KADBASE: interfacing expert systems with databases' IEEE Expert Vol 4 No 3 (1989) pp 65-76 A knowledge-aided database management system prototype called KADBASE is described. K A D B A S E is a flexible interface in which multiple databases and knowledge-aided database systems can communicate as independent, self-descriptive components within a loosely coupled distributed engineering computer system. The authors describe the final architecture of their working prototype, demonstrate its use in engineering applications, and provide examples from two civil engineering knowledge-based systems: SPEX, a structural component design system, and HICOST, a building-cost estimator.
Tomiyama, T and Ten Hagen, P J W 'Representing knowledge in two distinct descriptions: extensional versus intentional' Artif. Intell. Eng. Vol 5 No 1 (January 1990) pp 23-32 A theory of knowledge is described on which CAD systems can be based. Two distinct description methods--extensional and intensional--are presented and then compared in the context of CAD applications. It is shown that extensional description methods are more suitable for a future intelligent CAD system due to their data streams being frequently modified. Intensional description methods are found to be better in performing other tasks, such as simple queries. The paper ends by proposing a new data description method. 117