abstract = "Genetic Programming explores the problem search space
by means of operators and selection. Mutation and
crossover operators apply uniformly, while selection is
the driving force for the search. Constrained GP
changes the uniform exploration to pruned non-uniform,
skipping some subspaces and giving preferences to
others, according to some heuristics. Adaptable
Constrained GP is a methodology for discovery of such
useful heuristics. Both methodologies have previously
demonstrated their surprising capabilities using only
first-order (parent-child) heuristics. Recently, they
have been extended to second-order (parent-children)
heuristics. This paper describes the second-order
processing, and illustrates the usefulness and
efficiency of this approach using a simple problem
specifically constructed to exhibit strong second-order
structure.",
notes = "University of Missouri-St Louis St. Louis, MO 63121
Also known as \cite{2002066} Distributed on CD-ROM at
GECCO-2011.