We are developing a swarm-intelligent inspection system based on a swarm of autonomous, miniature robots, using only on-board, local sensors. To estimate intrinsic advantages and limitations of the proposed possible distributed control solution, we capture the dynamic of the system at a higher abstraction level using non-spatial probabilistic microscopic and macroscopic models. In a previous publication, we showed that we are able to predict quantitatively the performances of the swarm of robots for a given metric and a beaconless policy. In this paper, after briefly reviewing our modeling methodology, we explore the effect of adding an additional state to the individual robot controller, which allow robots to serve as a beacon for teammates and therefore bias their inspection routes. Results show that this additional complexity helps the swarm of robots to be more efficient in terms of energy consumption but not necessarily in terms of time required to complete the inspection. We also demonstrate that a beacon-based policy introduces a strong coupling among the behavior of robots, coupling which in turn results in nonlinearities at the macroscopic model level.