Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
A comparison of bloat control methods for genetic programming
Evolutionary Computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Repeated patterns in tree genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
The Role of Population Size in Rate of Evolution in Genetic Programming
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
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Measuring fitness progression using numeric quantification in an Evolutionary Computation (EC) system may not be sufficient to capture the rate of evolution precisely. In this paper, we define the rate of evolution Rein an EC system based on the rate of efficient genetic variations being accepted by the EC population. This definition is motivated by the measurement of "amino acid to synonymous substitution ratio" ka/ksin biology, which has been widely accepted to measure the rate of gene sequence evolution. Experimental applications to investigate the effects of four major configuration parameters on our rate of evolution measurement show that Rewell reflects how evolution proceeds underneath fitness development and provides some insights into the effectiveness of EC parameters in evolution acceleration.