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A comparison of LISP and MUMPS as implementation languages for knowledge-based systems.

A C Curtis

    Journal of Medical Systems
    |October 1, 1984
    PubMed
    Summary

    This study explores programming languages for knowledge-based systems, comparing LISP and MUMPS. It suggests MUMPS extensions to enhance its artificial intelligence capabilities.

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    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Programming Languages

    Background:

    • Knowledge-based systems (KBS) are crucial in artificial intelligence.
    • Effective implementation relies on suitable programming language features.
    • LISP and MUMPS are prominent languages in this domain.

    Purpose of the Study:

    • To summarize key components of knowledge-based systems.
    • To compare LISP and MUMPS for KBS development.
    • To propose MUMPS enhancements for AI applications.

    Main Methods:

    • Literature review of KBS components and programming language features.
    • Comparative analysis of LISP and MUMPS.
    • Identification of potential MUMPS language extensions.

    Main Results:

    • Key programming language features for KBS implementation identified.
    • LISP and MUMPS evaluated as platforms for KBS.
    • Specific suggestions for MUMPS extensions provided.

    Conclusions:

    • MUMPS can be enhanced for AI applications without compromising its core nature.
    • Careful language selection and adaptation are vital for successful KBS development.

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