Ant-based clustering is a nature-inspired technique whereas stochastic agents perform the task of clustering high-dimensional data. This paper analyzes the popular technique of Lumer/Faieta. It is shown that the Lumer/Faieta approach is strongly related to Kohonen's SelfOrganizing Batch Map. A unifying basis is derived in order to assess strengths and weaknesses of both techniques. The behaviour of several popular ant-based clustering techniques is explained.