Many expert systems have moved out of development laboratories into field test and routine use. About sixty such systems are listed. Academic research laboratories are contributing manpower to fuel the commercial development of AI. But the quantity of AI research may decline as a result unless the applied systems are experimented with and analyzed.

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Expert systems: working systems and the research literature

Expert system projects are often based on collaboration with single domain expert. This leads to difficulties in judging the suitability of the chosen task and in acquiring the detailed knowledge required to carry out the task. This anecdotal article considers some of the advantages of using a diverse collection of domain experts.

/pdf/knowledge-acquisition-from-multiple-experts-e88g9l1azi.pdf

Knowledge Acquisition from Multiple Experts

As expert system technology spreads, the need for verification of system knowledge assumes greater importance. This paper addresses the issues involved in demonstrating a rule-based system to be free from error. A holistic perspective is adopted, wherein sorces, manifestations, and effects of errors are identified. A general taxonomy is created, and the implications for system performance and development outlined. Existing strategies for knowledge verification are surveyed, their applicability assessed, and some directions for systematic verification suggested.

Issues in the verification of knowledge in rule-based systems

We discuss commercial expert system development, using our experience with the Dipmeter Advisor system as a case study. While the data is too sparse for definitive results, several ideas have emerged as important and suggestive as guidelines for subsequent commercial expert system undertakings.

During the past four years, the Dipmeter Advisor system has migrated from an initial experiment in application of expert system techniques in well-log interpretation to a candidate commercial interpretation system. The system has undergone substantial change: It has been implemented in different configurations, in different languages, and on different computer systems. Our ability to experiment with the system has been greatly enhanced by the tools and ideas of rapid prototyping. We have also observed an oscillation in thrust over time between (i) expansion and change in the domain knowledge, and 00 selection and design of appropriate expert system tools. Finally, we have found several of the maxims of expert system development to be valid, but question a number of others.

/pdf/the-dipmeter-advisor-system-a-case-study-in-commercial-3yre4us3jj.pdf

The dipmeter advisor system: a case study in commercial expert system development

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The dipmeter advisor system: a case study in commercial expert system development