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| C. FERREIRA |
In E. Lutton, J. A. Foster, J. Miller, C. Ryan, and A. G. B. Tettamanzi, eds., Proceedings of the 4th European Conference on Genetic Programming, Lecture Notes in Computer Science, Vol. 2278, pages 51-60, Springer-Verlag, Berlin, Germany, 2002.
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Discovery of the Boolean Functions to the Best Density-Classification Rules Using Gene Expression Programming
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| Experimental Setup |
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The total 27 = 128 transition states of each rule consists of the fitness cases used to evaluate fitness. In all cases, the set of functions
F = { N, A, O, X, D, R, I, M} (representing, respectively, NOT, AND, OR, XOR, NAND, NOR, IF, and Majority, where the first is a function of one argument, the second through fifth are functions of two arguments, and the last two are functions of three arguments), and the set of terminals
T = {c, b, a, u, 1, 2, 3}. The fitness fi of a program
i is evaluated by the equation:
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(9) |
where n is the number of fitness cases correctly evaluated, and
Ct is the total number of fitness cases. Thus, for the entire set of fitness cases,
fmax = 128.
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