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Fully Distributed Cartesian Genetic Programming

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Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection (PAAMS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13616))

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.

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Authors and Affiliations

  1. University of Oldenburg, 26129, Oldenburg, Germany

    Jörg Bremer & Sebastian Lehnhoff

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  1. Jörg Bremer
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  2. Sebastian Lehnhoff
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Correspondence to Jörg Bremer .

Editor information

Editors and Affiliations

  1. Umeå University, Umeå, Sweden

    Frank Dignum

  2. University of Lille, Lille, France

    Philippe Mathieu

  3. University of Salamanca, Salamanca, Spain

    Juan Manuel Corchado

  4. University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

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Bremer, J., Lehnhoff, S. (2022). Fully Distributed Cartesian Genetic Programming. In: Dignum, F., Mathieu, P., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection. PAAMS 2022. Lecture Notes in Computer Science(), vol 13616. Springer, Cham. https://doi.org/10.1007/978-3-031-18192-4_4

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  • DOI: https://doi.org/10.1007/978-3-031-18192-4_4

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  • Online ISBN: 978-3-031-18192-4

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