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Bat Algorithm Swarm Robotics Approach for Dual Non-cooperative Search with Self-centered Mode

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Intelligent Data Engineering and Automated Learning – IDEAL 2018 (IDEAL 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11315))

Abstract

This paper presents a swarm robotics approach for dual non-cooperative search, where two robotic swarms are deployed within a map with the goal to find their own target point, placed at an unknown location of the map. We consider the self-centered mode, in which each swarm tries to solve its own goals with no consideration to any other factor external to the swarm. This problem, barely studied so far in the literature, is solved by applying a popular swarm intelligence method called bat algorithm, adapted to this problem. Five videos show some of the behavioral patterns found in our computational experiments.

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References

  1. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)

    Google Scholar 

  2. Suárez, P., Iglesias, A., Gálvez, A.: Make robots be bats: specializing robotic swarms to the bat algorithm. Swarm and Evolutionary Computation (in press)

    Google Scholar 

  3. https://goo.gl/JUbBYw, (password: RobotsIDEAL2018)

  4. Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 65–74. Springer, Berlin (2010). https://doi.org/10.1007/978-3-642-12538-6_6

    Chapter  Google Scholar 

  5. Yang, X.S., Gandomi, A.H.: Bat algorithm: a novel approach for global engineering optimization. Eng. Comput. 29(5), 464–483 (2012)

    Article  Google Scholar 

  6. Yang, X.S., He, X.: Bat algorithm: literature review and applications. Int. J. Bio-Inspired Comput. 5(3), 141–149 (2013)

    Article  Google Scholar 

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Acknowledgements

Research supported by project PDE-GIR of the European Union’s Horizon 2020 (Marie Sklodowska-Curie grant agreement No. 778035), grant #TIN2017-89275-R (Spanish Ministry of Economy and Competitiveness, Computer Science National Program, AEI/FEDER, UE), grant #JU12 (SODERCAN and European Funds FEDER UE) and project EMAITEK (Basque Government).

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Authors and Affiliations

  1. University of Cantabria, Avenida de los Castros s/n, 39005, Santander, Spain

    Patricia Suárez, Akemi Gálvez & Andrés Iglesias

  2. Toho University, 2-2-1 Miyama, Funabashi, 274-8510, Japan

    Akemi Gálvez & Andrés Iglesias

  3. University of Maribor, Smetanova ulica 17, 2000, Maribor, Slovenia

    Iztok Fister & Iztok Fister Jr.

  4. TECNALIA, Derio, Spain

    Eneko Osaba & Javier Del Ser

  5. University of the Basque Country (UPV/EHU), Bilbao, Spain

    Javier Del Ser

  6. Basque Center for Applied Mathematics (BCAM), Bilbao, Spain

    Javier Del Ser

Authors
  1. Patricia Suárez
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  2. Akemi Gálvez
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  3. Iztok Fister
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  4. Iztok Fister Jr.
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  5. Eneko Osaba
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  6. Javier Del Ser
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  7. Andrés Iglesias
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Corresponding author

Correspondence to Andrés Iglesias .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, UK

    Hujun Yin

  2. Rm 209, Building B, Autonomous University of Madrid, Madrid, Spain

    David Camacho

  3. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Seville, Seville, Spain

    Antonio J. Tallón-Ballesteros

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Suárez, P. et al. (2018). Bat Algorithm Swarm Robotics Approach for Dual Non-cooperative Search with Self-centered Mode. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11315. Springer, Cham. https://doi.org/10.1007/978-3-030-03496-2_23

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  • DOI: https://doi.org/10.1007/978-3-030-03496-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03495-5

  • Online ISBN: 978-3-030-03496-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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