Identifying long-term success issues of expert systems

Abstract This investigation identifies issues associated with the long-term success of expert systems and the specific nature of maintenance. Open-ended structured interviews were conducted with several expert system developers to assess factors critical to the long-term success of expert systems. The interviews provide an opportunity to examine the developer's perspective. Questions regarding general expert system issues and questions addressing maintenance-specific issues were the basis for the interviews. The interviews were analyzed by three reviewers, and the results were aggregated to create a list of relevant issues associated with long-term success of expert systems. Maintenance, verification and validation, case-based reasoning, realistic user expectations, and problem definition were the five most identified issues. Perceptions of expert systems maintenance were specifically investigated. The dynamic nature of systems was mentioned most often as a critical issue for maintaning expert systems. Results from this investigation provide an awareness of the issues associated with long-term maintenance of expert systems and its relative importance for an expert system development methodology.

[1]  David S. Prerau,et al.  Maintainability techniques in developing large expert systems , 1990, IEEE Expert.

[2]  Richard P. Will,et al.  True and false dependence on technology: Evaluation with an expert system , 1991 .

[3]  Daniel G. Bobrow,et al.  Expert systems: perils and promise , 1986, CACM.

[4]  Elias M. Awad,et al.  The systems analyst as a knowledge engineer: can the transition be successfully made? , 1990, SIGBDP '90.

[5]  Efraim Turban,et al.  Decision Support and Expert Systems: Management Support Systems , 1990 .

[6]  David S. Prerau.  Selection of an Appropriate Domain for an Expert System , 1985, AI Mag..

[7]  Floyd J. Fowler,et al.  Survey Research Methods , 1984 .

[8]  Nigel W. Bryant.  Managing expert systems , 1988 .

[9]  L. G. Hull,et al.  Expert system development methodology and management , 1991, [1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs.

[10]  Arnoud De Meyer,et al.  Managing Expert Systems: a Framework and Case Study , 1990, Inf. Manag..

[11]  David W. Rolston.  Principles of Artificial Intelligence and Expert Systems Development , 1988 .

[12]  F. J. Fowler,et al.  Standardized Survey Interviewing: Minimizing Interviewer-Related Error. , 1989 .

[13]  John J. Sviokla.  An examination of the impact of expert systems on the firm: the case of XCON , 1990 .

[14]  Paul Alpar.  Toward structured expert systems development , 1990 .

[15]  James C. Wetherbe,et al.  A comparison of perceptions about information center success , 1991, Inf. Manag..

[16]  E. Turban.  Review of expert systems technology , 1988 .

[17]  Johanna D. Moore,et al.  Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development , 1984, IEEE Transactions on Software Engineering.

[18]  Richard P. Will,et al.  A review of barriers to expert system diffusion , 1990, SIGBDP '90.

[19]  Efraim Turban,et al.  Integrating Expert Systems and Decision Support Systems , 1986, MIS Q..

[20]  H. Raghav Rao,et al.  Technology transfer: making expert systems commercially successful , 1992, IEEE Expert.

[21]  Larry R. Medsker,et al.  The expert system life cycle: what have we learned from software engineering? , 1990, SIGBDP '90.