Title
Validation of knowledge-based systems: a reassessment of the field
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
ISSN
0269-2821
Recommended Citation
"Validation of knowledge-based systems: a reassessment of the field" (2015). Faculty Bibliography 2010s. 6416.
https://stars.library.ucf.edu/facultybib2010/6416
Comments
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