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.",