Pseudo-hierarchical ant-based clustering using a heterogeneous agent hierarchy and automatic boundary formation

Authors:
Jeremy B. Brown;Manfred Huber
Affiliations:
The University of Texas at Arlington, Arlington, TX, USA;The University of Texas at Arlington, Arlington, TX, USA
Venue:
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Year:
2010

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Abstract

The behavior and self-organization of ant colonies provides a promising model to address distributed clustering. However, most ant-based clustering approaches suffer from inefficiencies due to large numbers of unproductive ant movements and inefficient cluster merging, leading them to produce too many clusters and to converge too slowly. To address these issues, this paper presents a new ant-based clustering algorithm in which ants are organized in a loose two-level hierarchy with worker ants maintaining movement zone boundaries around each cluster and organizing its internal structure while a single queen ant in each cluster is responsible for moving items between clusters by directly handing them to other queens. This provides an infrastructure that avoids excessive ant movements between cluster regions while allowing for efficient long distance cluster merging. Comparison of this approach with traditional ant-based clustering shows its promise to significantly improve performance and scalability.