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AUSAI
2006
Springer

Data Clustering and Visualization Using Cellular Automata Ants

9 years 9 months ago
Data Clustering and Visualization Using Cellular Automata Ants
This paper presents two novel features of an emergent data visualization method coined "cellular ants": unsupervised data class labeling and shape negotiation. This method merges characteristics of ant-based data clustering and cellular automata to represent complex datasets in meaningful visual clusters. Cellular ants demonstrates how a decentralized multi-agent system can autonomously detect data similarity patterns in multi-dimensional datasets and then determine the according visual cues, such as position, color and shape size, of the visual objects accordingly. Data objects are represented as individual ants placed within a fixed grid, which decide their visual attributes through a continuous iterative process of pair-wise localized negotiations with neighboring ants. The characteristics of this method are demonstrated by evaluating its performance for various benchmarking datasets.
Andrew Vande Moere, Justin James Clayden, Andy Don
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where AUSAI
Authors Andrew Vande Moere, Justin James Clayden, Andy Dong
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