Vitorino Ramos, Fernando Muge, Pedro Pina, Self-Organized Data and
Image Retrieval as a Consequence of Inter-Dynamic Synergistic
Relationships in Artificial Ant Colonies, in Javier Ruiz-del-Solar,
Ajith Abraham and Mario Köppen (Eds.), Frontiers in Artificial
Intelligence and Applications, IOS/Press, Vol. 87, ISBN 1 5860 32976,
pp. 500-509, Dec. 2002.
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
clustering, 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: Ant Systems, Unsupervised Clustering, Data and Image
Retrieval, Data Mining, Distributed Computing, Collective Decision
Support Systems.
best, Vitorino
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