A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering...

The Flocking model, first proposed by Craig Reynolds, is one of the
first bio-inspired computational collective behavior models that has many
popular applications, such as animation. Our early research has resulted in a
flock clustering algorithm that can achieve better performance than the Kmeans
or the Ant clustering algorithms for data clustering. This algorithm
generates a clustering of a given set of data through the embedding of the highdimensional data items on a two-dimensional grid for efficient clustering result retrieval and visualization. In this paper, we propose a bio-inspired clustering model, the Multiple Species Flocking clustering model (MSF), and present a distributed multi-agent MSF approach for document clustering.