+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+ Symbolic regression (symbreg): A simple GP example with Open BEAGLE Copyright (C) 2001-2003 by Christian Gagne and Marc Parizeau +=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+ Getting started =============== Example is compiled in binary 'symbreg'. Usage options is described by executing it with command-line argument '-OBusage'. The detailed help can also be obtained with argument '-OBhelp'. Objective ========= Find a function of one independent variable and one dependent variable, in symbolic form, that fits a given sample of 20 $(x_i,y_i)$ data points, where the target function is the quadratic polynomial $x^4 + x^3 + x^2 + x$. Terminal set ============ X (the independent variable) PI Ephemeral constants randomly generated in $[-1,1]$ Function set ============ + - * / (protected division) SIN COS EXP LOG (protected logarithm) Fitness cases ============= The given sample of 20 data points $(x_i,y_i)$, randomly chosen within interval [-1,1]. Fitness ======= $\frac{1.}{1.+RMSE}$ where RMSE is the Root Mean Square Error on the fitness cases. Stopping criteria ================= When the evolution reaches the maximum number of generations. Reference ========= John R. Koza, "Genetic Programming: On the Programming of Computers by Means of Natural Selection", MIT Press, 1992, pages 162-169.