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Swarming agents for distributed pattern detection and classification

By Sven A. Brueckner, H. Van and Dyke Parunak

Abstract

Swarming agents in networks of physically distributed processing nodes may be used for data acquisition, data fusion, and control applications. We present an architecture for active surveillance systems in which simple mobile agents collectively process realtime data from heterogeneous sources at or near the origin of the data. We motivate the system requirements with the needs of a surveillance system for the early detection of large-scale bioterrorist attacks on a civilian population, but the same architecture is applicable to a wide range of other domains. The pattern detection and classification processes executed by the proposed system emerge from the coordinated activities of agents of two populations in a shared computational environment. Detector agents draw each other’s attention to significant spatiotemporal patterns in the observed data stream. Classifier agents rank the detected patterns according to their respective criterion. The resulting system-level behavior is adaptive, robust, and scalable

Topics: Fine-Grained Agents, Swarm Intelligence, Stigmergy, Self-Organization, Biosurveillance Application
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.195.9462
Provided by: CiteSeerX
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