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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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
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