  In this paper, we investigate the quest for a single target, that remains
fixed in a lattice, by a set of independent walkers. The target exhibits a
fluctuating behavior between trap and ordinary site of the lattice, whereas the
walkers perform an intermittent kind of search strategy. Our searchers carry
out their movements in one of two states between which they switch randomly.
One of these states (the exploratory phase) is a symmetric nearest neighbor
random walk and the other state (relocating phase) is a symmetric next-nearest
neighbor random walk. By using the multistate continuous-time random-walk
approach we are able to show that for dynamical targets, the intermittent
strategy (despite the simplicity of the kinetics chosen for searching) improves
detection, in comparison to displacements in a single state. We have obtained
analytic results, that can be numerically evaluated, for the Survival
Probability and for the Lifetime of the target. Thus, we have studied the
dependence of these quantities both in terms of the transition probability that
describes the dynamics of the target and in terms of the parameter that
characterizes the walkers' intermittency. In addition to our analytical
approach, we have implemented Monte Carlo simulations, finding excellent
agreement between the theoretical--numerical results and simulations.
