Validation of knowledge-based systems: a reassessment of the field

    Authors

    F. A. Batarseh;A. J. Gonzalez

    Comments

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    Abbreviated Journal Title

    Artif. Intell. Rev.

    Keywords

    Knowledge-based systems; Validation; Lifecycle model; Software testing; Test cases; INTELLIGENT SYSTEMS; VERIFICATION; PERFORMANCE; Computer Science, Artificial Intelligence

    Abstract

    The subject of validation and verification (V&V) of knowledge-based systems (KBS) has been one of decreasing importance in the last decade. Research and development in the field reduced drastically. One of the main reasons is the persistent software challenges and failures. These failures have been categorized in different ways. One initiative however, which most researchers in the field agree upon, is that the only way to eliminate these problems is by rigorously performing V&V. Although there have been vast improvements in the field of V&V methodology, studies indicate that KBS industry still lacks rigorous validation methods. In this paper, we review the most important validation paradigms described in literature for KBS during the years of their fame. Additionally, this article studies the significant methods, aims to reassess these methods in light of recent advances, and propose new future directions for validation of KBS.

    Journal Title

    Artificial Intelligence Review

    Volume

    43

    Issue/Number

    4

    Publication Date

    1-1-2015

    Document Type

    Article

    Language

    English

    First Page

    485

    Last Page

    500

    WOS Identifier

    WOS:000351112300002

    ISSN

    0269-2821

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