Аннотация
A cellular genetic programming approach to data
classification is proposed. The method uses cellular
automata as a framework to enable a fine-grained
parallel implementation of GP through the diffusion
model. The main advantages to employ the method for
classification problems consist in handling large
populations in reasonable times, enabling fast
convergence by reducing the number of iterations and
execution time, favouring the cooperation in the search
for good solutions, thus improving the accuracy of the
method.
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