abstract = "Much recent progress in Genetic Programming (GP) can
be ascribed to work in semantic GP, which facilitates
program induction by considering program behaviour on
individual fitness cases. It is therefore interesting
to consider whether alternative decompositions of
fitness cases might also provide useful information.
The one we present here is motivated by work in
analogical reasoning. So-called proportional analogies
(gills are to fish as lungs are to mammals) have a
hierarchical relational structure that can be captured
using the formalism of Structural Information Theory.
We show how proportional analogy problems can be solved
with GP and, conversely, how analogical reasoning can
be engaged in GP to provide for problem decomposition.
The idea is to treat pairs of fitness cases as if they
formed a proportional analogy problem, identify
relational consistency between them, and use it to
inform the search process.",