A Detailed Analysis of a PushGP Run

Abstract

In evolutionary computation runs there is a great deal of data that could be saved and analysed. This data is often put aside, however, in favour of focusing on the final outcomes, typically captured and presented in the form of summary statistics and performance plots. Here we examine a genetic programming run in detail and trace back from the solution to determine how it was derived. To visualize this genetic programming run, the ancestry graph is extracted, running from the solution(s) in the final generation up to their ancestors in the initial random population. The key instructions in the solution are also identified, and a genetic ancestry graph is constructed, a subgraph of the ancestry graph containing only those individuals contributed genetic information (or instructions) to the solution. This visualization and our ability to trace these key instructions throughout the run allowed us to identify general inheritance patterns and key evolutionary moments in this run.