5 research outputs found
A study of the methodologies currently available for the maintenance of the knowledge-base in an expert system
This research studies currently available maintenance methodologies for expert system knowledge bases and taxonomically classifies them according to the functions they perform. The classification falls into two broad categories. These are: (1) Methodologies for building a more maintainable expert system knowledge base. This section covers techniques applicable to the development phases. Software engineering approaches as well as other approaches are discussed. (2) Methodologies for maintaining an existing knowledge base. This section is concerned with the continued maintenance of an existing knowledge base. It is divided into three subsections. The first subsection discusses tools and techniques which aid the understanding of a knowledge base. The second looks at tools which facilitate the actual modification of the knowledge base, while the last secttion examines tools used for the verification or validation of the knowledge base. Every main methodology or tool selected for this study is analysed according to the function it was designed to perform (or its objective); the concept or principles behind the tool or methodology: and its implementation details. This is followed by a general comment at the end of the analysis. Although expert systems as a rule contain significant amount of information related to the user interface, database interface, integration with conventional software for numerical calculations, integration with other knowledge bases through black boarding systems or network interactions, this research is confined to the maintenance of the knowledge base only and does not address the maintenance of these interfaces. Also not included in this thesis are Truth Maintenance Systems. While a Truth Maintenance System (TMS) automatically updates a knowledge base during execution time, these update operations are not considered \u27maintenance\u27 in the sense as used in this thesis. Maintenance in the context of this thesis refers to perfective, adaptive, and corrective maintenance (see introduction to chapter 4). TMS on the other hand refers to a collection of techniques for doing belief revision (Martin, 1990) . That is, a TMS maintains a set of beliefs or facts in the knowledge base to ensure that they remain consistent during execution time. From this perspective, TMS is not regarded as a knowledge base maintenance tool for the purpose of this study
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AI Techniques in Software Engineering
The idea of using artificial intelligence techniques to support programming has been around for a long time. The earliest notion was to avoid programming entirely. The human user would just tell the computer what to do, without saying how to do it, and the computer would do the right thing. Even if this were feasible, however, it would be much too tedious, since each time the user would have to repeat the details of what he wanted done. So the goal of programming was to explain things to the computer only once, and then later on be able to tell the computer to do the same thing again in some short form, such as the name of the "program." Thus the idea evolved that a user would somehow tell the computer what program was desired, and the computer would write down the program in some internal form so that it could be remembered and repeated later. The assumption was that the resulting program would be correct, complete, efficient, easy to use, and so forth. It would also be exactly what the human user wanted
College Catalog, 2011-2012
https://digitalcommons.buffalostate.edu/buffstatecatalogs/1221/thumbnail.jp
Umetnost Soluna i balkanskih zemalja i duhovni tokovi u XIV veku
Éditions spéciales 31. Institut des Études balkaniques. Académie serbe des Sciences et des Art