Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions

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@InProceedings{Husa:2023:evostarLBA,

• author = "Jakub Husa and Lukas Sekanina",
• title = "Semantic Mutation Operator for Fast and Efficient Design of {Bent Boolean} Functions",
• booktitle = "Evostar 2023 Late breaking abstracts",
• year = "2023",
• editor = "Antonio M. Mora and Anna I. Esparcia-Alcazar",
• pages = "30--33",
• address = "Brno",
• month = "12-14 " # apr,
• organisation = "Species",
• keywords = "genetic algorithms, genetic programming, Semantic Mutation, Bent Boolean Functions",
• URL = "https://arxiv.org/abs/2403.13950",
• size = "4 pages",
• abstract = "Bent functions are a type of Boolean functions with properties that make them useful in cryptography. In this paper we propose a new semantic mutation operator for design of bent Boolean functions via genetic programming. To assess the efficiency of the proposed operator, we compare it to several other commonly used non-semantic mutation operators. Our results show that semantic mutation makes the evolutionary process more efficient, and significantly decreases the number of fitness function evaluations required to find a bent function.",

}

Genetic Programming entries for Jakub Husa Lukas Sekanina

Citations