Towards a Cognitive Design Pattern for Collective Decision-Making

  • Andreagiovanni Reina
  • Marco Dorigo
  • Vito Trianni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8667)

Abstract

We introduce the concept of cognitive design pattern to provide a design methodology for distributed multi-agent systems. A cognitive design pattern is a reusable solution to tackle problems requiring cognitive abilities (e.g., decision-making, attention, categorisation). It provides theoretical models and design guidelines to define the individual control rules in order to obtain a desired behaviour for the multi-agent system as a whole. In this paper, we propose a cognitive design pattern for collective decision-making inspired by the nest-site selection behaviour of honeybee swarms. We illustrate how to apply the pattern to a case study involving spatial factors: the collective selection of the shortest path between two target areas. We analyse the dynamics of the multi-agent system and we show a very good agreement with the predictions of the macroscopic model.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Babaoğlu, O., Canright, G., Deutsch, A., Di Caro, G., Ducatelle, F., Gambardella, L.M., Ganguly, N., Jelasity, M., Montemanni, R., Montresor, A., Urnes, T.: Design patterns from biology for distributed computing. Transactions on Adaptive and Autonomous Systems 1(1), 26–66 (2006)CrossRefGoogle Scholar
  2. 2.
    Campo, A., Garnier, S., Dédriche, O., Zekkri, M., Dorigo, M.: Self-Organized Discrimination of Resources. PLoS One 6(5), e19888 (2011)Google Scholar
  3. 3.
    Codling, E.A., Plank, M.J., Benhamou, S.: Random walk models in biology. Journal of the Royal Society, Interface 5(25), 813–834 (2008)CrossRefGoogle Scholar
  4. 4.
    Couzin, I.: Collective cognition in animal groups. Trends in Cognitive Sciences 13(1), 36–43 (2009)CrossRefGoogle Scholar
  5. 5.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional (1995)Google Scholar
  6. 6.
    Gardelli, L., Viroli, M., Omicini, A.: Design patterns for self-organising systems. In: Burkhard, H.-D., Lindemann, G., Verbrugge, R., Varga, L.Z. (eds.) CEEMAS 2007. LNCS (LNAI), vol. 4696, pp. 123–132. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Hamann, H.: Towards swarm calculus: Urn models of collective decisions and universal properties of swarm performance. Swarm Intelligence 7(2-3), 145–172 (2013)CrossRefGoogle Scholar
  8. 8.
    Marshall, J.A.R., Bogacz, R., Dornhaus, A., Planqué, R., Kovacs, T., Franks, N.R.: On optimal decision-making in brains and social insect colonies. Journal of the Royal Society, Interface 6(40), 1065–1074 (2009)CrossRefGoogle Scholar
  9. 9.
    Montes, M., Ferrante, E., Scheidler, A., Pinciroli, C., Birattari, M., Dorigo, M.: Majority-rule opinion dynamics with differential latency: A mechanism for self-organized collective decision-making. Swarm Intelligence 5(3-4), 305–327 (2010)CrossRefGoogle Scholar
  10. 10.
    Nelson, W.: Hazard plotting for incomplete failure data. Journal of Quality Technology 1, 27–52 (1969)Google Scholar
  11. 11.
    Pais, D., Hogan, P.M., Schlegel, T., Franks, N.R., Leonard, N.E., Marshall, J.A.R.: A mechanism for value-sensitive decision-making. PLoS One 8(9), e73216 (2013)Google Scholar
  12. 12.
    Parker, C.A.C., Zhang, H.: Cooperative decision-making in decentralized multiple-robot systems: the best-of-N problem. IEEE Transactions on Mechatronics 14(2), 240–251 (2009)CrossRefGoogle Scholar
  13. 13.
    Seeley, T.D., Visscher, P.K., Schlegel, T., Hogan, P.M., Franks, N.R., Marshall, J.A.R.: Stop signals provide cross inhibition in collective decision-making by honeybee swarms. Science 335(6064), 108–111 (2012)CrossRefGoogle Scholar
  14. 14.
    Trianni, V., Tuci, E., Passino, K.M., Marshall, J.A.R.: Swarm Cognition: An interdisciplinary approach to the study of self-organising biological collectives. Swarm Intelligence 5(1), 3–18 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Andreagiovanni Reina
    • 1
  • Marco Dorigo
    • 1
  • Vito Trianni
    • 2
  1. 1.IRIDIA, CoDE, Université Libre de BruxellesBrusselsBelgium
  2. 2.ISTCItalian National Research CouncilRomeItaly

Personalised recommendations