Efficient clustering with fuzzy ants

In the past decade, various clustering algorithms based on the behaviour of real ants were proposed. The main advantage of these algorithms lies in the fact that no additional information, such as an initial partitioning of the data or the number of clusters, is needed. In this paper we show how the combination of the ant-based approach with fuzzy rules leads to an algorithm which is conceptually simpler, more efficient and more robust than previous approaches.