Vadidation of authentic reasoning expert systems
| Autor: | Laurie Webster, Jen-Gwo Chen, Simon S. Tan, Carolyn Watson, Andre de Korvin |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Information Systems and Management
Computer science business.industry Fuzzy set Legal expert system Model-based reasoning computer.software_genre Machine learning Expert system Computer Science Applications Theoretical Computer Science Conjunction (grammar) Task (project management) Artificial Intelligence Control and Systems Engineering Rough set Artificial intelligence business computer Software |
| Zdroj: | Information Sciences. 117:19-46 |
| ISSN: | 0020-0255 |
| DOI: | 10.1016/s0020-0255(99)00005-5 |
| Popis: | This paper outlines an approach for validating the expert system's performance by comparing the expert system to the consensus results of the experts (i.e., using several experts to solve the same problem that the authentic reasoning expert system solved). We also discuss a mathematical process that includes the use of rough set theory as a means of capturing and quantifying the reasoning factors and reasoning processes of the experts. Additionally, a generalized entropy criterion for measuring consensus effectiveness based on Dempster–Shafer's theory of mathematical evidence is used in conjunction with rough set and fuzzy set theories. This is used for ascertaining whether or not the behavior of the expert system is evident in the behavior of the experts which is an essential task in validating authentic reasoning expert systems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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