Agents Clustering with Ants

G. Simon and D.Fournier

Laboratoire Informatique du Havre (EA3219) 25 rue Philippe Lebon BP 540, 76058 Le Havre, France {gsimon@iut.univ-lehavre.fr, Dominique.Fournier@univ-lehavre.fr}

keywords

Emergence, Agents Organisations, Simulation, Clustering, Ants.

1 introduction

1.1 Simulation and Emergent Structures

The work presented in this paper takes place in the context of the analysis of the global behaviour of an agents population. This agents population can be made of implicit and/or explicit organisations. Explicit organisations are statically defined at the design step as in Aalaadin model for example (Ferber and Gutknecht 1998) in terms of groups and roles. As a consequence, each agent may interact with others according to these organisations. On the contrary, implicit organisations appear during the execution of the multi-agent system and can evolve with time. They correspond to a particular behaviour and/or state of a subset of agents resulting from the current state of the system and from the context in which its execution takes place. Such phenomena are observed very often in multi-agent systems and especially in simulation ones. Indeed, in the simulation domain, the goal is to design multi-agents systems being able to reflect the behaviour of real entities and to manage multiple kinds of interactions between them. These interactions can lead to emergent (Cariani 1992; Jean 1997) phenomena. In (Servat et al. 1998a), Servat summarises characteristics of an emergent phenomenon as follows : ”First the emergence phenomenon lies to a certain extent in a shift of our vision of things. Secondly, emergent phenomena reveal a shift in the behaviour of the whole”. Thus, emergent phenomena appearing inside a simulation are often the expression of a significant evolution in the world which is simulated. More precisely, these emergent phenomena are generally made of aggregations of quite similar agents which correspond to a higher description level of the simulated world. They represent some kinds of abstractions of some parts of these worlds.

For example, in MANTA (Drogoul et al. 1995), a multi-agent simulation of ants societies, a kind of division of work between ants appear. This distribution is not coded in the behaviour of each ant. However, these emergent social groups can be of interest to understand the behaviour of an ants society.

References

Cariani, P. 1992. Emergence and artificial life. In Langton et Al

editors Artificial Life II, pages 775-797, Addi sson-Wesley. Drogoul, A.; Corbara, B. and Lalande, S. 1995. MANTA: new experimental results on the emergence of (artificial) ant societies. In artificial societies: The Computer Simulation of Social Life, pages 190-211, Conte and Gilbert editors. Ferber, J. and Gutknecht, O. 1998. Aalaadin: a meta-model for the analysis and design of organizations in multi-agent systems. In ICMAS’98.

Jean, M. R. 1997. Emergence et SMA. In Proceedings of the

5th JFIADSMA. Hermes. Servat, D.; Perrier, É.; Treuil, J. and Drogoul, A. 1998a. When agents emerge from agents: introducing multi-scale viewpoints in multi-agent simulations. In Conte and Gilbert, editors, LNAI series, volume 1534. Springer-Verlag.