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Model-Based Reasoning in Science and Technology pp 381–392Cite as

Emergent Semiotics in Genetic Programming and the Self-Adaptive Semantic Crossover

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 314))

Abstract

We present SASC, Self-Adaptive Semantic Crossover, a new class of crossover operators for genetic programming. SASC operators are designed to induce the emergence and then preserve good building-blocks, using meta-control techniques based on semantic compatibility measures. SASC performance is tested in a case study concerning the replication of investment funds.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Statistics, University of São Paulo, Brazil

    Rafael Inhasz & Julio Michael Stern

Authors
  1. Rafael Inhasz
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  2. Julio Michael Stern
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Editor information

Editors and Affiliations

  1. Università di Pavia, Pavia, Italy

    Lorenzo Magnani

  2. CLE State University of Campinas, Campinas, Brazil

    Walter Carnielli

  3. Università di Siena, Siena, Italy

    Claudio Pizzi

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Inhasz, R., Stern, J.M. (2010). Emergent Semiotics in Genetic Programming and the Self-Adaptive Semantic Crossover. In: Magnani, L., Carnielli, W., Pizzi, C. (eds) Model-Based Reasoning in Science and Technology. Studies in Computational Intelligence, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15223-8_21

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  • DOI: https://doi.org/10.1007/978-3-642-15223-8_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15222-1

  • Online ISBN: 978-3-642-15223-8

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