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Ant algorithms and flocking algorithms are the two main programming paradigms in swarm intelligence. They are built on stochastic models, widely used in optimization problems. However, though this modeling leads to highperformance algorithms, some mechanisms, like the symmetry break in ant decision, are still not well understood at the local ant level. Moreover, there is currently no modeling approach which joins the two paradigms. This paper proposes an entirely novel approach to thedoi:10.1109/saso.2007.1 dblp:conf/saso/CharrierBC07 fatcat:qgaewnsdkva6hl62oy2xr4xm4m