Frequency analysis for dendritic cell population tuning

R Oates, G Kendall, JM Garibaldi - Evolutionary Intelligence, 2008 - Springer
Evolutionary Intelligence, 2008Springer
The dendritic cell algorithm (DCA) has been applied successfully to a diverse range of
applications. These applications are related by the inherent uncertainty associated with
sensing the application environment. The DCA has performed well using unfiltered signals
from each environment as inputs. In this paper we demonstrate that the DCA has an
emergent filtering mechanism caused by the manner in which the cell accumulates its
internal variables. Furthermore we demonstrate a relationship between the migration …
Abstract
The dendritic cell algorithm (DCA) has been applied successfully to a diverse range of applications. These applications are related by the inherent uncertainty associated with sensing the application environment. The DCA has performed well using unfiltered signals from each environment as inputs. In this paper we demonstrate that the DCA has an emergent filtering mechanism caused by the manner in which the cell accumulates its internal variables. Furthermore we demonstrate a relationship between the migration threshold of the cells and the transfer function of the algorithm. A tuning methodology is proposed and a robotic application published previously is revisited using the new tuning technique.
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