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Cartesian genetic programming approach for embryonic fabric architecture

The Cartesian genetic programming (CGP) considers grid of nodes to represent a genotype. In the corresponding phenotype each node represents a processing element. The processing element has similar structure as of smallest embryonic fabric element. It can be an embryonic molecule where all molecules combine and create an embryonic cell equivalent to a circuit. The evolutionary algorithm applied to genotypes select the fittest. The evaluated genotype determines the configuration data for embryonic cell. The configuration data generation is automated with this approach. As well this can lead to optimized embryonic fabric structure if optimization by evolutionary algorithm is utilized. In this paper the CGP approach is applied to generate configuration data for embryonic fabric. The approach is simulated for 1-bit adder circuit.