Several researchers have used Price's equation (from biology theory literature) to analyze the various components of an Evolutionary Algorithm (EA) while it is running, giving insights into the components contributions and interactions. While their results are interesting, they are also limited by the fact that Price's equation was designed to work with the averages of population fitness. The EA practitioner, on the other hand, is typically interested in the best individuals in the population, not the average.In this paper we introduce an approach to using Price's equation which instead calculates the upper tails of population distributions. By applying Price's equation to EAs that use survival selection instead of parent selection, this information is calculated automatically.
['Jeffrey K. Bassett', 'Mitchell A. Potter', 'Kenneth A. De Jong']
Applying price's equation to survival selection