Download Fuzzy Logic in Artificial Intelligence: IJCAI’97 Workshop by Lotfi A. Zadeh (auth.), Anca L. Ralescu, James G. Shanahan PDF

By Lotfi A. Zadeh (auth.), Anca L. Ralescu, James G. Shanahan (eds.)

This quantity constitutes the completely refereed post-workshop complaints of a world workshop on fuzzy common sense in synthetic Intelligence held in Negoya, Japan in the course of IJCAI '97.
The 17 revised complete papers provided have passed through rounds of reviewing and revision. 3 papers by means of prime experts within the sector are dedicated to the overall relevance of fuzzy good judgment and fuzzy units to AI. the rest papers deal with a number of correct matters starting from conception to software in components like wisdom illustration, induction, good judgment programming, robotics, development reputation, etc.

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Extra info for Fuzzy Logic in Artificial Intelligence: IJCAI’97 Workshop Nagoya, Japan, August 23–24, 1997 Selected and Invited Papers

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We use an example set to obtain a relative frequency by counting the number of objects of class C which lie in the cell corresponding to rl, r2 feature values. This number divided by the total number of examples of class C will give an estimate for this probability. It is this counting procedure which we wish to modify in the case where the intervals are fuzzy rather than crisp. Let the feature spaces R1 and R2 each be divided into a mutually exclusive set of fuzzy sets, fA ..... fE for R1 and fa .....

Here we simply define it as using computing methods that compute with words in addition to numbers and symbols. To date computer methods have used only numbers and symbols. Words have some behaviour like symbols and some behaviour like numbers. They can be manipulated like symbols in a purely syntactic manner but we can also use their semantic content to provide different measures of comparison, counting and arithmetic calculations similar to the way we use numbers. The sort of words which we are talking about are words which can be given to predicate variables.

Baldwin, ,I. F. (1992b). "The Management of Fuzzy and Probabilistic Uncertainties for Knowledge Based Systems" in Encyclopaedia of AI, Ed. S. A. Shapiro, John Wiley. ) 528-537. Baldwin, J. F. (1993b). " Asia-Pacific Engineering Journal 3:59-81. Baldwin, J. F. 993a). "Fuzzy, Probabilistic and Evidential Reasoning in Fill", Proc. 2nd IEEE International Conference on Fuzzy Systems, San Francisco, CA, 459-464. (ISBN 0-7803-0614-7). Baldwin, ,1. F. (1993). "Fuzzy Sets, Fuzzy Clustering, and Fuzzy Rules in AI" in Fuzzy Logic in AI, Ed.

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