On the Effectiveness of Genetic Operations in Symbolic Regression
This provides incremental insights into genetic programming efficiency for researchers in evolutionary computation.
The paper tackled the problem of understanding evolutionary dynamics in genetic programming by analyzing genealogical information, diversity measures, and fitness variation, and found that only a small fraction of ancestors contribute to the best solutions.
This paper describes a methodology for analyzing the evolutionary dynamics of genetic programming (GP) using genealogical information, diversity measures and information about the fitness variation from parent to offspring. We introduce a new subtree tracing approach for identifying the origins of genes in the structure of individuals, and we show that only a small fraction of ancestor individuals are responsible for the evolvement of the best solutions in the population.