abstract = "We propose a crossover operator that works with
genetic programming trees and is approximately
geometric crossover in the semantic space. By defining
semantic as program's evaluation profile with respect
to a set of fitness cases and constraining to a
specific class of metric-based fitness functions, we
cause the fitness landscape in the semantic space to
have perfect fitness-distance correlation. The proposed
approximately geometric semantic crossover exploits
this property of the semantic fitness landscape by an
appropriate sampling. We demonstrate also how the
proposed method may be conveniently combined with hill
climbing. We discuss the properties of the methods, and
describe an extensive computational experiment
concerning logical function synthesis and symbolic
regression.",
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).