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2004). The strength of these systems lies in their ability to put expert knowledge to practical use when an expert is not available. Expert systems make knowledge more widely available and help overcome the problem of translating knowledge into practical, useful results. ES architecture contains four basic components: (a) a specialized Knowledge Base that stores the relevant knowledge about the domain of expertise; (b) an Inference Engine, which is used to reason about specific problems, for example using production rules or multipleattribute decision-making models; (c) a working memory, which records facts about the real world; and (d) an interface that allows user-system interaction, as depicted in Figure 2.

Fuzzy Multicriteria Model for Ergonomic workplace analysis and Risk analysis. Information Technology, Knowledge Management and Engineering for Enterprise Productivity and Quality of Working Life (International Conference: Computer-Aided Ergonomics and Safety - CAES'05), Kosice-Slovak Republic. Nunes, I. L. (2006a). ERGO_X - The Model of a Fuzzy Expert System for Workstation Ergonomic Analysis. International Encyclopedia of Ergonomics and Human Factors. Karwowski, CRC Press: 3114-3121. Nunes, I.

Fuzzy Logic, Knowledge and Natural Language 17 5. Probabilistic and Fuzzy Logic in distinct sides of knowledge I think that the fuzzy interpretation, proposed by Kosko, of the wave-function |ψ|2 in Schrödinger’s equation is very interesting. Indeed it seems to me that Schrödinger’s equation regards the quantity and the quantum distribution of matter, and not the probability to find the particle in the region dV. However, in other fields of science it is not useful to try to reduce probabilistic logic to Fuzzy Logic or to treat the problems of probability with Fuzzy Logic.

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