Calculating the Unknown

Figure 5.13: Calculating the unknown success

In the real world is the success set $G^{+}$ not known. One has to 'approach' this unknown set by 'searching' it. If we assume the genotype as some n-dimensional coordinates in a n-dimensional space then are the values of the real evaluation function $eval'()$ some additional space $ran(eval'())$ which includes the world $W$ as a parameter. Because the real world $W$ can change through time we have to assume that the 'ideal' success set is not necessarily a 'fixed' set; the ideal success set can change too! For some finiteduration one can assume that the success set $G^{+}$ is stable and the evaluation function $eval'()$ is then an empirical estimate of the evaluation function $eval^{+}()$.