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- W2020194387 abstract "This paper presents two methods for self-adapting the semantic sensitivities in a recently proposed semantics-based crossover: Semantic Similarity based Crossover (SSC). The first self-adaptation method is inspired by a self-adaptive method for controlling mutation step size in Evolutionary Strategies (1/5 rule). The design of the second takes into account more of our previous experimental observations, that SSC works well only when a certain portion of events successfully exchange semantically similar subtrees. These two proposed methods are then tested on a number of real-valued symbolic regression problems, their performance being compared with SSC using predetermined sensitivities and with standard crossover. The results confirm the benefits of the second self-adaption method." @default.
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- W2020194387 date "2010-07-01" @default.
- W2020194387 modified "2023-10-14" @default.
- W2020194387 title "Self-adapting semantic sensitivities for Semantic Similarity based Crossover" @default.
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- W2020194387 doi "https://doi.org/10.1109/cec.2010.5586052" @default.
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