Abstract
We look at how the structure of social networks and the nature of social interactions affect the behaviour of Particle Swarms Optimisers. To this end, we propose a general model of communication and consensus which focuses on the effects of social interactions putting the details of the dynamics and the optimum seeking behaviour of PSOs into the background.
Work supported by EPSRC XPS grant GR/T11234/01.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mendes, R., Neves, J.: What makes a successful society? Experiments with population topologies in particle swarms. In: Bazzan, A.L.C., Labidi, S. (eds.) SBIA 2004. LNCS, vol. 3171, pp. 346–355. Springer, Heidelberg (2004)
Mendes, R., Kennedy, J., Neves, J.: The fully informed particle swarm: Simpler, maybe better. IEEE Transactions of Evolutionary Computation 8(3), 204–210 (2004)
Mendes, R., Kennedy, J., Neves, J.: Avoiding the pitfalls of local optima: How topologies can save the day. In: Proceedings of the 12th Conference Intelligent Systems Application to Power Systems (ISAP2003), Lemnos, Greece, IEEE Computer Society Press, Los Alamitos (2003)
van den Bergh, F.: An Analysis of Particle Swarm Optimizers. PhD thesis, Department of Computer Science, University of Pretoria, Pretoria, South Africa (2001)
Baxter, N., Collings, D., Adjali, I.: Agent-based modelling – intelligent customer relationship management. BT Technology Journal 21(2), 126–132 (2003)
Poli, R., Langdon, W.B., Marrow, P., Kennedy, J., Clerc, M., Bratton, D., Holden, N.: Communication, leadership, publicity and group formation in particle swarms. Technical Report CSM-453, Department of Computer Science, University of Essex (2006)
Kennedy, J.: Bare bones particle swarms. In: Proceedings of the IEEE Swarm Intelligence Symposium (SIS) 2003, Indianapolis, Indiana, pp. 80–87 (2003)
Langdon, W.B., Poli, R., Holland, O., Krink, T.: Understanding particle swarm optimisation by evolving problem landscapes. In: Gambardella, L.M., Arabshahi, P., Martinoli, A. (eds.) Proceedings SIS 2005 IEEE Swarm Intelligence, pp. 30–37. IEEE, Pasadena, California, USA (2005)
Langdon, W.B., Poli, R.: Evolving problems to learn about particle swarm and other optimisers. In: Corne, D., Michalewicz, Z., Dorigo, M., Eiben, G., Fogel, D., Fonseca, C., Greenwood, G., Chen, T.K., Raidl, G., Zalzala, A., Lucas, S., Paechter, B., Willies, J., Guervos, J.J.M., Eberbach, E., McKay, B., Channon, A., Tiwari, A., Volkert, L.G., Ashlock, D., Schoenauer, M. (eds.) Proceedings of the 2005 IEEE Congress on Evolutionary Computation, vol. 1, pp. 81–88. IEEE Press, Edinburgh, UK (2005)
Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation 6(1), 58–73 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Poli, R. et al. (2006). Communication, Leadership, Publicity and Group Formation in Particle Swarms. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_12
Download citation
DOI: https://doi.org/10.1007/11839088_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38482-3
Online ISBN: 978-3-540-38483-0
eBook Packages: Computer ScienceComputer Science (R0)