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95/105= 0.91


1,1

Competition and synergy patterns in nonhomogeneous ant-colony lattices.

doi: 10.6062/jcis.2015.06.03.0099

(Free PDF)

Authors

J. C. Becceneri, R. Sautter, N. L. Vijaykumar and C.P. Camilo.

Abstract

In this paper we introduce, for the first time, an Ant Colony System (ACS) composed of two different populations of agents. The first population has more agents than the second while the second has more energy than the first. The agents are distributed in a square lattice according to their corresponding population. In our first approach of this nonhomogeneous system the formation and evolution of competition and synergy patterns are described by means of the Gradient Pattern Analysis (GPA) technique. Based on several preliminary results we discuss a new game prototype whose laws of success and convergence are given by means of symmetry breaking patterns in a nonhomogeneous (4x4) lattice.

Keywords

Intelligent agents, ant colony system, gradient pattern analysis, game theory, comp. mathematics.

References

[1] Banabeau, E., Social insect colonies as complex adaptative systems, Ecosystems 1: 437-443, 1998. doi: 10.1007/s100219900038

[2] Banabeau, E., Dorigo, M., Theraulaz, G. Inspiration for optimization from social insect behaviour, Nature 406: 39-42, 2000. doi:10.1038/35017500

[3] Dorigo, M. Optimization, learning and natural algorithms. Ph.D. Thesis, Politecnico di Milano, Italy, 1992.

[4] Dorigo, M., Gambardella, L.M. Ant colonies for the travelling salesman problem, Biosystems 43: 73-81, 1997.

[5] da Silva, A.F., Rosa, R.R., Roman, L.S., Veje, E., Pepe, I. Characterization of asymmetric fragmentation patterns in SFM images of porous silicon, Solid State Commun 113: 703-708, 2000.

[6] Jones, D.F., Mirrazavi, S.K., Tamiz, M., Multi-objective meta-heuristics: An overview of the current state-of-the-art, European Journal of Operational Research 1: 1-9, 2002.

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