Hostname: page-component-6bb9c88b65-fsdjw Total loading time: 0 Render date: 2025-07-26T15:08:23.262Z Has data issue: false hasContentIssue false
  • English
  • Français

Knowledge-acquisition tools with explicit problem-solving models

Published online by Cambridge University Press:  07 July 2009

William Birmingham  and
Georg Klinker
William Birmingham
Affiliation:
University of Michigan, Department of Electrical Engineering and Computer Science, Ann Arbor, MI 48109, USA (e.mail: wpb@crim.eecs.umich.edu)
Georg Klinker
Affiliation:
Digital Equipment Corporation, 111 Locke Drive, Marlboro, MA 01752, USA (e.mail: klinker@airg.dec.com)
Get access Rights & Permissions [Opens in a new window]

Abstract

In the past decade, expert systems have been applied to a wide variety of application tasks. A central problem of expert system development and maintenance is the demand placed on knowledge engineers and domain experts. A commonly proposed solution is knowledge-acquisition tools. This paper reviews a class of knowledge-acquisition tools that presuppose the problem-solving method, as well as the structure of the knowledge base. These explicit problem-solving models are exploited by the tools during knowledge-acquisition, knowledge generalization, error checking and code generation.

Information

Type
Research Article
Information
The Knowledge Engineering Review , Volume 8 , Issue 1 , March 1993 , pp. 5 - 25
Copyright
Copyright © Cambridge University Press 1993

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Balkany, A, Birmingham, W and Tommelein, I, 1991. “A knowledge-level analysis of several design tools”. In: Proceedings AI and Design 1991, Edinburgh, UK.Google Scholar
Birmingham, WP, Gupta, A and Siewiorek, D, 1992. Automating the Design of Computer Systems: The Micon Project, Jones and Barlett.CrossRefGoogle Scholar
Birmingham, WP, Gupta, AP and Siewiorek, DP, 1989. “The micon system for computer design”. In: 26th Design Automation Conference Proceedings, IEEE Computer Society.Google Scholar
Birmingham, W, 1988. “Automated knowledge acquisition for a computer hardware synthesis system”. In: Proceedings 3rd Knowledge Acquisition for Knowledge-based Systems Workshop, Banff, Canada.Google Scholar
Boose, J, 1984. “Personal construct theory and the transfer of human expertise”. In: Proceedings 4th National Conference on Artificial Intelligence, Austin, TX.Google Scholar
Boose, J, 1989. “A survey of knowledge acquisition techniques and tools” Knowledge acquisition 1(1) 3–38.CrossRefGoogle Scholar
Buchanan, B and Feigenbaum, E, 1978. “Dendral and metadendral: their applications dimensions” Artificial Intelligence 11.CrossRefGoogle Scholar
Chandrasekaran, B, 1990. “Design problem solving: A task analysis” Al Magazine 11(4) 54–71.Google Scholar
Clancey, W, 1984. “Heuristic classification” Artificial Intelligence 27 289–350.CrossRefGoogle Scholar
Dallemagne, G, Klinker, G, Marques, D, McDermott, J and Tung, D, 1992. “Making application programming more worthwhile”. In: Schmalhofer, F, Strube, G and Wetter, Th, (eds.), Knowledge Engineering and Cognition, Springer-Verlag.Google Scholar
Davis, R, 1981. “Interactive transfer of expertise: acquisition of new inference rules” Artificial Intelligence 12 (2) 121–157.CrossRefGoogle Scholar
Diederich, J, Ruhmann, I and May, M, 1987. ‘Kriton: a knowledge acquisition tool for export systems” International Journal of Man-Machine Studies 6 (1) 29–40.CrossRefGoogle Scholar
Duda, R and Reboh, R, 1984. “Al and decision making: the prospector experience”. In: Reitman, W (ed), Artificial Intelligence Applications for Business, Ablex.Google Scholar
Eshelman, L, Ehret, D, McDermott, J and Tan, M, 1987. “MOLE: a tenacious knowledge acquisition tool” International Journal of Man-Machine Studies 26 (1) 41–54.CrossRefGoogle Scholar
Forgy, CL, 1984. “The OPS83 Report”. Technical Report, CMU-CS-84-133, School of Computer Science, Carnegie Mellon University.Google Scholar
Forgy, CL, 1981. “OPS5 User's Manual”. Technical Report, CMU-CS-81-135, School of Computer Science, Carnegie Mellon University.Google Scholar
Friedland, PE and Iwasaki, Y, 1989. “The concept and implementation of skeletal plans” Journal of Automated Reasoning 1 (2) 161–208.Google Scholar
Gruber, T and Cohen, P, 1987. “Design for acquisition: principles of knowledge system design to facilitate knowledge acquisition” International Journal of Man-Machine Studies 26 (2) 143–159.CrossRefGoogle Scholar
Klinker, G, Boyd, C, Dong, D, Maiman, J, McDermott, J and Schnelbach, R, 1989. “Building expert systems with KNACK” Knowledge Acquisition 1(3) 299–320.CrossRefGoogle Scholar
Klinker, G, 1988. “KNACK: sample-driven knowledge acquisition for reporting systems”. In: Marcus, S, (ed.), Automating Knowledge Acquisition for Expert Systems, Kluwer.Google Scholar
Linster, M, 1989. “Towards a second generation knowledge-acquisition tool” Knowledge Acquisition 1 (2) 163–184.CrossRefGoogle Scholar
Marcus, S, 1988. SALT: a knowledge-acquisition tool for purpose-and-revise systems”. In: Marcus, S, (ed.), Automating Knowledge Acquisition for Expert Systems, Kluwer.CrossRefGoogle Scholar
Marques, D, Dallemagne, G, Klinker, G, McDermott, J and Tung, D, 1992. “Easy programming: Empowering people to build their own applications” IEEE Expert 7 (3) 16–29.CrossRefGoogle Scholar
Marques, D, Klinker, G, Dallemagne, G, Gautier, P, McDermott, J and Tung, D, 1991. “More data on usable and reusable programming constructs”. In: Proceedings 6th Knowledge Acquisition for Knowledge-based Systems Workshop, Banff, Canada.Google Scholar
Marques, D, Latto, A and McDermott, J, 1988 “A comparison of case based reasoning with few large vs many small features”. In: Proceedings of the Workshop on Case Based Reasoning, St Paul.Google Scholar
McDermott, J, 1988. “Preliminary steps toward a taxonomy of problem-solving methods”. In: Marcus, S, (ed.), Automating Knowledge Acquisition for Expert Systems, Kluwer.Google Scholar
McDermott, J, 1982. “RI: a rule-based configurer of computer systems” Artificial Intelligence 19 (1).CrossRefGoogle Scholar
Mitchell, T, Mahadevan, S and Steinberg, L, 1985. “LEAP: A learning apprentice for VLSI design”. In: Proceedings of IJCAJ 85. Morgan Kaufman.Google Scholar
Musen, M, 1989(a). “An editor for the conceptual models of interactive knowledge acquisition tools” International Journal of Man-Machine Studies 31 (6) 673–699.CrossRefGoogle Scholar
Musen, M, 1989(b). Automated Generation of Model-Based Knowledge-Acquisition Tools, Pitman.Google Scholar
Newell, A, 1982. “The knowledge level” Artificial Intelligence 18 87–127.CrossRefGoogle Scholar
Offutt, D, 1988. “SIZZLE: A knowledge-acquisition tool specialized for the sizing task”. In: Marcus, S, (ed), Automating Knowledge Acquisition for Expert Systems, Kluwer.Google Scholar
Rich, C and Waters, R, 1990. The Programmer's Apprentice, Addison-Wesley.Google Scholar
Runkel, JT, Birmingham, WP, Darr, TP, Maxim, BR and Tommelein, ID, 1992. “Domain independent design system: Environment for rapid development of configuration design systems”. In: 2nd International Conference on AI in Design, Butterworth-Heinemann Ltd., UK.Google Scholar
Shaw, MLG and Gaines, BR, 1987. “Techniques for knowledge acquisition and transfer” International Journal of Man-Machine Studies 27 (3) 251–280.CrossRefGoogle Scholar
Shortliffe, EH, 1986. “Medical expert systems–Knowledge tools for physicians” West Journal of Medicine 145 830–839.Google ScholarPubMed
Steels, L. 1990. “Components of expertise” Al Magazine 11 (2).Google Scholar
Tu, S, Shahar, Y, Dawes, J, Winkles, J, Puerta, A and Musen, M, 1991. “A problem-solving model for episodic skeletal-plan refinement”. In: Proceedings 6th Knowledge Acquisition of Knowledge-based Systems Workshop. Banff, Canada.Google Scholar
Tu, S, Kahn, M, Musen, M, Ferguson, J, Shortliffe, E and Fagan, L, 1989. “Episodic skeletal-plan refinement based on temporal data” Communications of the ACM 32 (12) 1439–1455.CrossRefGoogle Scholar
Westphal, C and McGraw, K, (eds.), 1989. Special Issue on Knowledge Acquisition, ACM SIGART 108.Google Scholar
Wielinga, B, Schreiber, ATh and Breuker, JA, 1992. “KADS: a modeling approach to knowledge engineering” Knowledge Acquisition 4 5–54.CrossRefGoogle Scholar