In this paper, we investigate the quest for a single target, which remains fixed in a lattice, by a set of independent walkers. The target exhibits fluctuating behavior between a trap and an 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 (the 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, which 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.
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