  This article deals with the spatio-temporal sensors deployment in order to
maximize detection probability of an intelligent and randomly moving target in
an area under surveillance. Our work is based on the rare events simulation
framework. More precisely, we derive a novel stochastic optimization algorithm
based on the generalized splitting method. This new approach offers promising
results without any state-space discretization and can handle various types of
constraints.
