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Lamarckian and Lifelong Memetic Search in Agent-Based Computing

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

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Abstract

Memetic algorithms when used with care can help in balancing exploitation and exploration of the metaheuristics, without the overhead measured by the rapidly increased number of function fitness calls. The paper tackles such balancing of use of metaheuristics in an agent-oriented setting. In particular, application of local search during a computing agent’s life is researched. The results shown for selected benchmark functions are presented along with necessary statistic testing.

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Acknowledgment

This research was supported by AGH University of Science and Technology Statutory Fund no. 11.11.230.124. This research was supported by PlGrid infrastructure.

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Authors and Affiliations

  1. Department of Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Krakow, Poland

    Wojciech Korczynski, Marek Kisiel-Dorohinicki & Aleksander Byrski

Authors
  1. Wojciech Korczynski
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  2. Marek Kisiel-Dorohinicki
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  3. Aleksander Byrski
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Corresponding author

Correspondence to Aleksander Byrski .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Korczynski, W., Kisiel-Dorohinicki, M., Byrski, A. (2017). Lamarckian and Lifelong Memetic Search in Agent-Based Computing. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_17

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  • DOI: https://doi.org/10.1007/978-3-319-55849-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55848-6

  • Online ISBN: 978-3-319-55849-3

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