A comparative analysis of methods for expert systems |
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| Affiliation: | 1. RIADI Laboratory, National School of Computer Sciences, Manouba University, La Manouba, 2010, Tunisia;2. High Institute of Telecommunication, Technoparc ElGhazala, Ariana, 2083, Tunisia;1. Electronics and Biomedical Engineering Faculty, Universidad Antonio Nariño, Carrera 3 Este No. 47A – 15 Bloque 4 Piso 1, Bogota, D.C., Colombia;2. Systems Engineering Faculty, Universidad Antonio Nariño, Bogota, D.C., Colombia;3. Tuberculosis Program, Santa Clara Hospital, Bogotá, D.C., Colombia;1. MIT School of Engineering (MIT SOE), MIT ADT University, Pune, Maharashtra, INDIA;2. Department of CSE, BITS Pilani, Dubai Campus, UNITED ARAB EMIRATES |
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| Abstract: | Given the current widespread interest in expert systems, it is important to examine the relative advantages and disadvantages of the various methods used to build them. In this paper we compare three important approaches to building decision aids implemented as expert systems: Bayesian classification, rule-based deduction, and frame-based abduction. Our critical analysis is based on a survey of previous studies comparing different methods used to build expert systems as well as our own collective experience over the last five years. The relative strengths and weaknesses of the different approaches are analysed, and situations in which each method is easy or difficult to use are identified. |
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