Evolutionary algorithms for designing reversible cellular automata
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{Mariot:GPEM,
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author = "Luca Mariot and Stjepan Picek and
Domagoj Jakobovic and Alberto Leporati",
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title = "Evolutionary algorithms for designing reversible
cellular automata",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2021",
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volume = "22",
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number = "4",
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pages = "429--461",
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month = dec,
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note = "Special Issue: Highlights of Genetic Programming 2020
Events",
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keywords = "genetic algorithms, genetic programming,
Shift-invariant transformations, Cellular automata,
Reversibility",
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ISSN = "1389-2576",
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URL = "https://rdcu.be/cyKGY",
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DOI = "doi:10.1007/s10710-021-09415-7",
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size = "33 pages",
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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.",
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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