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Leveraging Online Racing and Population Cloning in Evolutionary Multirobot Systems

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Applications of Evolutionary Computation (EvoApplications 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9598))

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Abstract

Online evolution of controllers on real robots typically requires a prohibitively long time to synthesise effective solutions. In this paper, we introduce two novel approaches to accelerate online evolution in multirobot systems. We introduce a racing technique to cut short the evaluation of poor controllers based on the task performance of past controllers, and a population cloning technique that enables individual robots to transmit an internal set of high-performing controllers to robots nearby. We implement our approaches over odNEAT, which evolves artificial neural network controllers. We assess the performance of our approaches in three tasks involving groups of e-puck-like robots, and we show that they facilitate: (i) controllers with higher performance, (ii) faster evolution in terms of wall-clock time, (iii) more consistent group-level performance, and (iv) more robust, well-adapted controllers.

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Notes

  1. 1.

    The source code of the experiments can be found at: http://fgsilva.com/?page_id=302.

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Acknowledgements

This work was partly supported by FCT under grants SFRH/BD/89573/2012, UID/EEA/50008/2013, and UID/Multi/04046/2013.

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Authors and Affiliations

  1. BioMachines Lab, Lisboa, Portugal

    Fernando Silva & Anders Lyhne Christensen

  2. Instituto de Telecomunicações, Lisboa, Portugal

    Fernando Silva & Anders Lyhne Christensen

  3. Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal

    Anders Lyhne Christensen

  4. BioISI, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal

    Fernando Silva & Luís Correia

Authors
  1. Fernando Silva
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  2. Luís Correia
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  3. Anders Lyhne Christensen
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Corresponding author

Correspondence to Fernando Silva .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Aalborg University, Copenhagen, Denmark

    Paolo Burelli

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Silva, F., Correia, L., Christensen, A.L. (2016). Leveraging Online Racing and Population Cloning in Evolutionary Multirobot Systems. In: Squillero, G., Burelli, P. (eds) Applications of Evolutionary Computation. EvoApplications 2016. Lecture Notes in Computer Science(), vol 9598. Springer, Cham. https://doi.org/10.1007/978-3-319-31153-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-31153-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31152-4

  • Online ISBN: 978-3-319-31153-1

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