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The feasibility of axiomatically-based expert systems.

¹Section on Medical Informatics, Stanford University School of Medicine, CA 94305-5479.

Computer Methods and Programs in Biomedicine

|October 1, 1989

Summary

Axiomatically-based expert systems, guided by decision theory, offer long-term benefits outweighing their slightly higher knowledge acquisition costs compared to traditional systems.

Area of Science:

Artificial Intelligence
Decision Science
Computer Science

Background:

Traditional expert systems lack rigorous theoretical foundations.
Axiomatically-based systems leverage established decision-making theories for enhanced performance.

Purpose of the Study:

To differentiate axiomatically-based expert systems from traditional ones.
To analyze the knowledge acquisition and computational demands of axiomatically-based systems.
To compare the development effort and long-term value of axiomatic versus traditional approaches.

Main Methods:

Comparative analysis of knowledge acquisition effort.
Quantitative comparison between existing and analogous axiomatically-based systems.
Evaluation of costs and benefits of the axiomatic approach.

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Main Results:

Axiomatically-based systems require a slightly greater initial knowledge acquisition effort.
The computational needs are analyzed in comparison to traditional systems.
Long-term benefits of the axiomatic approach are demonstrated to outweigh initial costs.

Conclusions:

The axiomatic approach provides significant long-term advantages in expert system design.
The enhanced rigor and theoretical grounding lead to superior system performance and reliability.
Investment in axiomatically-based systems is recommended for their superior value proposition.