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Grammar model-based program evolution.

, , , , , and . IEEE Congress on Evolutionary Computation, page 478-485. IEEE, (2004)

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Evolving approximations for the Gaussian Q-function by Genetic Programming with semantic based crossover., , , and . IEEE Congress on Evolutionary Computation, page 1-6. IEEE, (2012)Flexible representation for genetic programming : lessons from natural language processing.. University of New South Wales, Canberra, Australia, (2004)base-search.net (ftunswworks:oai:unsworks.unsw.edu.au:1959.4/38750).Evolving the best known approximation to the Q function., , , , , and . GECCO, page 807-814. ACM, (2012)Semantic based crossovers in Tree-Adjoining Grammar Guided Genetic Programming., , , and . RIVF, page 141-146. IEEE, (2013)Semantics based crossover for boolean problems., , , and . GECCO, page 869-876. ACM, (2010)Building on Success in Genetic Programming: Adaptive Variation and Developmental Evaluation., , , and . ISICA, volume 4683 of Lecture Notes in Computer Science, page 137-146. Springer, (2007)A study on Genetic Programming with layered learning and incremental sampling., , and . IEEE Congress on Evolutionary Computation, page 1179-1185. IEEE, (2011)Estimating the distribution and propagation of genetic programming building blocks through tree compression., , , , , and . GECCO, page 1011-1018. ACM, (2009)Solving Trigonometric Identities with Tree Adjunct Grammar Guided Genetic Programming.. HIS, page 339-351. Physica-Verlag, (2001)Using compression to understand the distribution of buildingblocks ingenetic programming populations., , , , and . IEEE Congress on Evolutionary Computation, page 2501-2508. IEEE, (2007)