Stigmergic Self-Organized Data and Image Retrieval

[Vitorino Ramos]

Self-Organized Data and Image Retrieval as a Consequence of
Inter-Dynamic Synergistic Relationships in Artificial Ant Colonies

PDF availabe in: http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_39.html

Abstract. Social insects provide us with a powerful metaphor to create
decentralized systems of simple interacting, and often mobile, agents. The
emergent collective intelligence of social insects - swarm intelligence -
resides not in complex individual abilities but rather in networks of
interactions that exist among individuals and between individuals and their
environment. The study of ant colonies behavior and of their
self-organizing capabilities is of interest to knowledge retrieval/
management and decision support systems sciences, because it provides
models of distributed adaptive organization which are useful to solve
difficult optimization, classification, and distributed control problems,
among others. In the present work we overview some models derived from the
observation of real ants, emphasizing the role played by stigmergy as
distributed communication paradigm, and we present a novel strategy
(ACLUSTER) to tackle unsupervised data exploratory analysis as well as data
retrieval problems. Moreover and according to our knowledge, this is also
the first application of ant systems into digital image retrieval problems.
Nevertheless, the present algorithm could be applied to any type of numeric
data.

Keywords: Swarm Intelligence, Ant Systems, Unsupervised Clustering, Data
and Image Retrieval, Data Mining, Distributed Computing, Collective
Decision Support Systems.

To appear with minor revisions at IOS PRESS, Hybrid Intelligent Systems,
Dec. 2002.


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