Fully Distributed Cartesian Genetic Programming 
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- @InProceedings{bremer:2022:PAAMS,
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  author =       "Joerg Bremer and Sebastian Lehnhoff",
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  title =        "Fully Distributed Cartesian Genetic Programming",
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  booktitle =    "Advances in Practical Applications of Agents,
Multi-Agent Systems, and Complex Systems Simulation.
The PAAMS Collection",
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  year =         "2022",
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  editor =       "Frank Dignum and Philippe Mathieu and 
Juan Manuel Corchado and Fernando {De La Prieta}",
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  volume =       "13616",
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  series =       "LNAI",
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  pages =        "36--49",
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  publisher =    "Springer",
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  keywords =     "genetic algorithms, genetic programming, Cartesian
Genetic Programming, parallel computing, Multi-agent
system, COHDA, Distributed optimization",
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  isbn13 =       "978-3-031-18192-4",
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  URL =          " https://rdcu.be/c7nZL", https://rdcu.be/c7nZL",
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  URL =          " http://link.springer.com/chapter/10.1007/978-3-031-18192-4_4", http://link.springer.com/chapter/10.1007/978-3-031-18192-4_4",
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  DOI =          " 10.1007/978-3-031-18192-4_4", 10.1007/978-3-031-18192-4_4",
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  size =         "14 pages",
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  abstract =     "Cartesian genetic programming is a popular version of
genetic programming and has meanwhile proven its
performance in many use cases. This paper introduces an
algorithmic level decomposition of program evolution
that can be solved by a multi-agent system in a fully
distributed manner. A heuristic for distributed
combinatorial problem solving is adapted to evolve
programs. The applicability of the approach and the
effectiveness of the multi-agent approach as well as of
the evolved genetic programs are demonstrated using
symbolic regression, n-parity, and classification
problems.",
- }
Genetic Programming entries for 
Joerg Bremer
Sebastian Lehnhoff
Citations
