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We present a context-aware algorithm based on ASM (Ants Sleeping Model) in order to resolve the clustering problem. In the ASM model data is represented by agents placed in a two dimensional grid. The agents will group themselves into clusters by making simple moves in their environment according to some local information the parameters being selected and adjusted adaptively. In order to avoid the agents to be trapped in local minima, they are also able to directly communicate with each other. Moreover, the agent moves are expressed by fuzzy IF- THEN rules and hence hybridization with a classical clustering algorithm is needless. Being aware of the context the agents can easily adapt when the environment changes.

Key words and phrases. fuzzy, clustering, ant.