Abstract
Communication among agents in swarm intelligent systems and more generally in multiagent systems, is crucial in order to coordinate agents’ activities so that a particular goal at the collective level is achieved. From an agent’s perspective, the problem consists in establishing communication policies that determine what, when, and how to communicate with others. In general, communication policies will depend on the nature of the problem being solved. This means that the solvability of problems by swarm intelligent systems depends, among other things, on the agents’ communication policies, and setting an incorrect set of policies into the agents may result in finding poor solutions or even in the unsolvability of problems. As a case study, this paper focus on the effects of letting agents use different communication policies in ant-based clustering algorithms. Our results show the effects of using different communication policies on the final outcome of these algorithms.
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
Bonabeau, E., Dorigo, M., Theralauz, G.: Swarm Intelligence. From Natural to Artificial Systems. Oxford University Press, Oxford (1999)
Deneubourg, J.-L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., Chretien, L.: The dynamics of collective sorting: Robot-like ants and ant-like robots. In: Proceedings of the First International Conference on Simulation of Adaptive Behavior: From Animals to Animats, pp. 356–365. MIT Press, Cambridge (1991)
Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5(2), 137–172 (1999)
Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)
Fritzke, B.: A growing neural gas network learns topologies. In: Advances in Neural Information Processing Systems 7. MIT Press, Cambridge (1995)
Grassé, P.-P.: La reconstruction du nid et les coordinations inter-individuelles chez bellicositermes natalensis et cubitermes sp. la theorie de la stigmergie: Essai d’interpretation des termites constructeurs. Insectes Sociaux 6(1), 41–83 (1959)
Handl, J., Knowles, J., Dorigo, M.: Ant-based clustering and topographic mapping. Artificial Life 11(2) (2005) (in press)
Handl, J., Meyer, B.: Improved ant-based clustering and sorting in a document retrieval interface. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 913–923. Springer, Heidelberg (2002)
Hettich, S., Blake, C.L., Merz, C.J.: UCI repository of machine learning databases (1998), http://www.ics.uci.edu/~mlearn/mlrepository.html
Holland, O., Melhuish, C.: Stigmergy, self-organization, and sorting in collective robotics. Artificial Life 5, 173–202 (1999)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Lumer, E.D., Faieta, B.: Diversity and adaptation in populations of clustering ants. In: Proceedings of the Third International Conference on Simulation of Adaptive Behavior: From Animals to Animats, vol. 3, pp. 501–508. MIT Press, Cambridge (1994)
Monmarché, N., Slimane, M., Venturini, G.: On improving clustering in numerical databases with artificial ants. In: Floreano, D., Mondada, F. (eds.) ECAL 1999. LNCS, vol. 1674, pp. 626–635. Springer, Heidelberg (1999)
Montes de Oca, M.A.: Effects on clustering quality of direct and indirect communication among agents in ant-based clustering algorithms. Master’s thesis, Instituto Tecnológico y de Estudios Superiores de Monterrey. Campus Monterrey (2005)
Montes de Oca, M.A., Garrido, L., Aguirre, J.L.: Efectos de la comunicación directa entre agentes en los algoritmos de agrupación de clases basados en el comportamiento de insectos sociales. Inteligencia Artificial 9(25), 59–69 (2005)
Montes de Oca, M.A., Garrido, L., Aguirre, J.L.: An hybridization of an ant-based clustering algorithm with growing neural gas networks for classification tasks. In: Proceedings of the 2005 ACM Symposium on Applied Computing, pp. 9–13. ACM Press, New York (2005)
Wilson, E.O.: The Insect Societies. The Belkap Press of Harvard University Press (1971)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Oca, M.A.M., Garrido, L., Aguirre, J.L. (2005). Effects of Inter-agent Communication in Ant-Based Clustering Algorithms: A Case Study on Communication Policies in Swarm Systems. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_26
Download citation
DOI: https://doi.org/10.1007/11579427_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
Online ISBN: 978-3-540-31653-4
eBook Packages: Computer ScienceComputer Science (R0)