Using Graph Databases to Explore the Dynamics of Genetic Programming Runs

Abstract

For both practical reasons and those of habit, most evolutionary computation research is presented in highly summary form. These summaries, however, often obscure or completely mask the profusion of specific selections, crossovers, and mutations that are ultimately responsible for the aggregate behaviours we are interested in. In this chapter we take a different approach and use the Neo4j graph database system to record and analyse the entire genealogical history of a set of genetic programming runs. We then explore a few of these runs in detail, discovering important properties of lexicase selection; these may in turn help us better understand the dynamics of lexicase selection, and the ways in which it differs from tournament selection. More broadly, we illustrate the value of recording and analysing this level of detail, both as a means of understanding the dynamics of particular runs, and as a way of generating questions and ideas for subsequent, broader study.