Program evolution of genetic programming based on probabilistic grammar

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In this research, we have proposed the “program evolution based on the probabilistic grammar” and constructed the automatic programming method by extending Genetic Programming (GP). In this population-based method, we do not employ genetic operators, such as crossovers or mutations. Instead, we estimate the probabilistic distribution of a probabilistic grammar, according to which a program is generated. We have validated the proposed method by applying to real-world problems, e.g., design automation, robotics, financial engineering, and Web intelligence etc.