An Evolutionary Metagraph Approach for Solving Problems in Complex Subject Areas
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- @InProceedings{Nardid:2025:REEPE,
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author = "Anatoly N. Nardid and Stepan S. Vinnikov and
Alexey V. Orazov and Yuriy E. Gapanyuk",
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title = "An Evolutionary Metagraph Approach for Solving
Problems in Complex Subject Areas",
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booktitle = "2025 7th International Youth Conference on Radio
Electronics, Electrical and Power Engineering (REEPE)",
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year = "2025",
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month = apr,
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming, CGP, linear genetic programming,
LGP, Power engineering, Directed acyclic graph,
Evolutionary computation, Benchmark testing,
Reproducibility of results, Complexity theory,
Standards, metagraphs, evolutionary algorithms,
directed acyclic graphs (DAGs))",
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ISSN = "2831-7262",
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DOI = "
doi:10.1109/REEPE63962.2025.10970829",
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abstract = "This paper explores the integration of metagraphs with
genetic programming (GP), offering a novel perspective
aimed at overcoming the limitations of traditional
graph-based approaches. Metagraphs, providing an
advanced abstraction over standard graphs, are examined
for their potential to more efficiently encapsulate
complex relationships and hierarchical structures. The
focus is on how metagraphs can contribute to
evolutionary algorithms by enriching the representation
of problem spaces, potentially leading to improved
adaptability and precision in solutions. We discuss the
initial theoretical insights and potential benefits of
this integration, positioning metagraphs as a promising
tool for enhancing the effectiveness of evolutionary
strategies. This exploration is intended to pave new
research pathways in GP, proposing that metagraphs hold
the potential to significantly augment the outcomes of
evolutionary processes.",
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notes = "Also known as \cite{10970829}",
- }
Genetic Programming entries for
Anatoly N Nardid
Stepan S Vinnikov
Alexey V Orazov
Yuriy E Gapanyuk
Citations