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    An Analysis of Semantic Aware Crossover


    Uy, Nguyen Quang and Hoai, Nguyen Xuan and O’Neill, Michael and McKay, Bob and Galván-López, Edgar (2009) An Analysis of Semantic Aware Crossover. Communications in Computer and Information Science, 51. pp. 56-65. ISSN 1865-0929

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    Abstract

    It is well-known that the crossover operator plays a very important role in genetic programming (GP). It is also widely admitted that standard crossover is made mostly randomly without semantic information. The lack of semantic information is the main reason that causes destructive effect, generally producing children worse than parents, of standard crossover. Recently, we have proposed a new semantic based crossover for GP, that is called Semantic Aware Crossover (SAC) [26]. It was shown in [26] that SAC outperforms standard crossover (SC) in solving a class of real-value symbolic regression problems. This paper extends [26] by giving some deeper analyses to understand why SAC helps to improve the performance of GP in solving these problems. The analyses show that SAC can increase the semantic diversity of population and this helps to reduce the crossover destructive effect in GP. The results also show that although SAC requires more time for checking semantics, this extra time is negligible.

    Item Type: Article
    Keywords: Semantic aware crossover; semantic; constructive effect; bloat;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15425
    Identification Number: https://doi.org/10.1007/978-3-642-04962-0_7
    Depositing User: Edgar Galvan
    Date Deposited: 07 Feb 2022 15:20
    Journal or Publication Title: Communications in Computer and Information Science
    Publisher: Springer
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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