By Peter Rein
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However, collaborative schemes could lead to a better behaviour. Therefore, a migration stage which enables the transfer of individuals among islands is generally incorporated. Four basic island-based models are seen to exist : all islands execute identical conﬁgurations (homogeneous), all islands execute diﬀerent conﬁgurations (heterogeneous), each island evaluates diﬀerent objective function subsets, and each island represents a diﬀerent region of the genotype or phenotype domains. In the ﬁrst two variants, the population of each island represents solutions to the same problem.
Fig. 5. Example of an individual found for Euclidean algorithm. The connections between outputs and inputs are shown as dashed arcs. 5 Conclusions We have shown that the standard CGP is capable of evolving simple iterative formulas. Based on training data, general well-known iterative formulas were automatically rediscovered for tasks of division and GCD. In comparison with classical symbolic regression problems , the computational eﬀort increased by approximately one order of magnitude.
The four first columns of Table 1 are the results of some base clustering algorithms. The results show that although each of these algorithms can obtain a good result over a specific dataset, it does not perform well over other datasets. But well setting of parameters of proposed method leads to its perfect superiority to most of well-known clustering algorithms. The only drawback of the proposed algorithm is the sensitivity to its two parameters. For a comprehensive study, look at the Fig 2 and Fig.
Cane sugar engineering by Peter Rein