Evolutionary algorithms for designing reversible cellular automata

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Mariot:GPEM,

• author = "Luca Mariot and Stjepan Picek and Domagoj Jakobovic and Alberto Leporati",
• title = "Evolutionary algorithms for designing reversible cellular automata",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2021",
• volume = "22",
• number = "4",
• pages = "429--461",
• month = dec,
• note = "Special Issue: Highlights of Genetic Programming 2020 Events",
• keywords = "genetic algorithms, genetic programming, Shift-invariant transformations, Cellular automata, Reversibility",
• ISSN = "1389-2576",
• URL = "https://rdcu.be/cyKGY",
• DOI = "doi:10.1007/s10710-021-09415-7",
• size = "33 pages",
• abstract = "Reversible Cellular Automata (RCA) are a particular kind of shift-invariant transformations characterized by dynamics composed only of disjoint cycles. They have many applications in the simulation of physical systems, cryptography, and reversible computing. we formulate the search of a specific class of RCA, namely, those whose local update rules are defined by conserved landscapes, as an optimization problem to be tackled with Genetic Algorithms (GA) and Genetic Programming (GP). In particular, our experimental investigation revolves around three different research questions, which we address through a single-objective, a multi-objective, and a lexicographic approach. In the single-objective approach, we observe that GP can already find an optimal solution in the initial population. This indicates that evolutionary algorithms are not needed when evolving only the reversibility of such CA, and a more efficient method is to generate at random syntactic trees that define the local update rule. On the other hand, GA and GP proved to be quite effective in the multi-objective and lexicographic approach to (1) discover a trade-off between the reversibility and the Hamming weight of conserved landscape rules, and (2) observe that conserved landscape CA cannot be used in symmetric cryptography because their Hamming weight (and thus their nonlinearity) is too low.",
• notes = "Cyber Security Research Group, Delft University of Technology, Mekelweg 2, Delft, The Netherlands",

}

Genetic Programming entries for Luca Mariot Stjepan Picek Domagoj Jakobovic Alberto Leporati

Citations