Analysing an Evolved Robotic Behaviour Using a Biological Model of Collegial Decision Making

  • Gianpiero Francesca
  • Manuele Brambilla
  • Vito Trianni
  • Marco Dorigo
  • Mauro Birattari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7426)

Abstract

Evolutionary robotics can be a powerful tool in studies on the evolutionary origins of self-organising behaviours in biological systems. However, these studies are viable only when the behaviour of the evolved artificial system closely corresponds to the one observed in biology, as described by available models. In this paper, we compare the behaviour evolved in a robotic system with the collegial decision making displayed by cockroaches in selecting a resting shelter. We show that artificial evolution can synthesise a simple self-organising behaviour for a swarm of robots, which presents dynamics that are comparable with the cockroaches behaviour.

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References

  1. 1.
    Nolfi, S., Floreano, D.: Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines. MIT Press, Cambridge (2000)Google Scholar
  2. 2.
    Adami, C.: Digital genetics: unravelling the genetic basis of evolution. Nature Reviews Genetics 7(2), 109–118 (2006)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Waibel, M., Keller, L., Floreano, D.: Genetic team composition and level of selection in the evolution of cooperation. IEEE Transactions on Evolutionary Computation 13(3), 648–660 (2009)CrossRefGoogle Scholar
  4. 4.
    Mitri, S., Floreano, D., Keller, L.: The evolution of information suppression in communicating robots with conflicting interests. Proceedings of the National Academy of Sciences 106(37), 15786–15790 (2009)CrossRefGoogle Scholar
  5. 5.
    Wischmann, S., Floreano, D., Keller, L.: Historical contingency affects signaling strategies and competitive abilities in evolving populations of simulated robots. Proceedings of the National Academy of Sciences 109(3), 864–868 (2012)CrossRefGoogle Scholar
  6. 6.
    Trianni, V., Nolfi, S.: Engineering the evolution of self-organizing behaviors in swarm robotics: A case study. Artificial Life 17(3), 183–202 (2011)CrossRefGoogle Scholar
  7. 7.
    Amé, J., Halloy, J., Rivault, C., Detrain, C., Deneubourg, J.-L.: Collegial decision making based on social amplification leads to optimal group formation. Proceedings of the National Academy of Sciences 103(15), 5835–5840 (2006)CrossRefGoogle Scholar
  8. 8.
    Garnier, S., Gautrais, J., Asadpour, M., Jost, C., Theraulaz, G.: Self-organized aggregation triggers collective decision making in a group of cockroach-like robots. Adaptive Behavior 17(2), 109–133 (2009)CrossRefGoogle Scholar
  9. 9.
    Campo, A., Garnier, S., Dédriche, O., Zekkri, M., Dorigo, M.: Self-organized discrimination of resources. PLoS ONE 6(5), e19888 (2011)Google Scholar
  10. 10.
    Brambilla, M., Pinciroli, C., Birattari, M., Dorigo, M.: Property-driven design for swarm robotics. In: Proceedings of 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), Richland, SC, pp. 139–146. IFAAMAS (2012)Google Scholar
  11. 11.
    Halloy, J., Sempo, G., Caprari, G., Rivault, C., Asadpour, M., Tâche, F., Said, I., Durier, V., Canonge, S., Amé, J.M., Detrain, C., Correll, N., Martinoli, A., Mondada, F., Siegwart, R., Deneubourg, J.-L.: Social integration of robots into groups of cockroaches to control self-organized choices. Science 318(5853), 1155–1158 (2007)CrossRefGoogle Scholar
  12. 12.
    Pinciroli, C., Trianni, V., O’Grady, R., Pini, G., Brutschy, A., Brambilla, M., Mathews, N., Ferrante, E., Caro, G.D., Ducatelle, F., Stirling, T., Gutiérrez, A., Gambardella, L.M., Dorigo, M.: ARGoS: a modular, multi-engine simulator for heterogeneous swarm robotics. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), pp. 5027–5034. IEEE Computer Society Press, Los Alamitos (2011)Google Scholar
  13. 13.
    Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., Magnenat, S., Zufferey, J., Floreano, D., Martinoli, A.: The e-puck, a robot designed for education in engineering, pp. 59–65. IPCB: Instituto Politécnico de Castelo Branco (2009)Google Scholar
  14. 14.
    Gutiérrez, Á., Campo, A., Dorigo, M., Donate, J., Monasterio-Huelin, F., Magdalena, L.: Open E-puck range & bearing miniaturized board for local communication in swarm robotics. In: ICRA 2009: Proceedings of the 2009 IEEE International Conference on Robotics and Automation, pp. 3111–3116. IEEE Press, Piscataway (2009)Google Scholar
  15. 15.
    Francesca, G., Brambilla, M., Trianni, V., Dorigo, M., Birattari, M.: Analysing an evolved robotic behaviour using a biological model of collegial decision making: Complete data (2012), Supplementary information page at http://iridia.ulb.ac.be/supp/IridiaSupp2012-009/

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gianpiero Francesca
    • 1
  • Manuele Brambilla
    • 1
  • Vito Trianni
    • 2
  • Marco Dorigo
    • 1
  • Mauro Birattari
    • 1
  1. 1.IRIDIA, CoDE, ULBBrusselsBelgium
  2. 2.ISTC-CNRRomeItaly

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