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Genetic Programming Bloat without Semantics

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Parallel Problem Solving from Nature PPSN VI (PPSN 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1917))

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Abstract

To investigate the fundamental causes of bloat, six artificial random binary tree search spaces are presented. Fitness is given by program syntax (the genetic programming genotype). GP populations are evolved on both random problems and problems with “building blocks”. These are compared to problems with explicit ineffective code (introns, junk code, inviable code). Our results suggest the entropy random walk explanation of bloat remains viable. The hard building block problem might be used in further studies, e.g. of standard subtree crossover.

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© 2000 Springer-Verlag Berlin Heidelberg

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Langdon, W.B., Banzhaf, W. (2000). Genetic Programming Bloat without Semantics. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_20

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  • DOI: https://doi.org/10.1007/3-540-45356-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41056-0

  • Online ISBN: 978-3-540-45356-7

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