Diagnostic Expert Systems Based on a Set Covering Model
作者： James A. Reggia , Dana S. Nau , Pearl Y. Wang
DOI: 10.1016/S0020-7373(83)80065-0
关键词: Generalization 、 Artificial intelligence 、 Computer science 、 Set (abstract data type) 、 Machine learning 、 Expert system 、 Basis (linear algebra)
摘要: This paper proposes that a generalization of the set covering problem can be used as an intuitively plausible model for diagnostic solving. Such is potentially useful basis expert systems in it provides solution to difficult multiple simultaneous disorders. We briefly introduce theoretical and then illustrate its application systems. Several challenging issues arise adopting real-world problems, these are also discussed along with solutions we have adopted.
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