This paper describes the use of an evolutionary algorithm to develop lookup tables which consist of an ordered list of regions, each of which encloses training examples of only one category. Compared to a simpler type of lookup table which consists of an unordered list of the training points and their categories, region based tables are smaller and, in general, faster to use. The development of a region based lookup table for the Frey and Slate character recognition problem is described and the size and accuracy achieved are compared with the original Frey and Slate point based lookup table. The reasons why it outperforms the original lookup table are discussed.
Lecture Notes in Computer Science : Methodology and Tools in Knowledge-Based Systems : Proceedings 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA-98-AIE), Benicassim, Castellon, Spain, 01-04 June 1998,
Vol. 1415, p. 640-646