Search decisions for teams of automata

The dynamics of exploration vs exploitation decisions are explored in the context of robotic search problems. Building on prior work on robotic search together with our own work on reactive control laws for potential field mapping, we propose a new set of search protocols for teams of sensor-enabled mobile robots. The focus is on collaborative strategies for the search of potential fields that are possibly time varying. We pose the problem of quickly finding regions where the potential achieves or exceeds a certain threshold. The search protocol has two distinct components. In an ¿exploration phase¿, agents execute either a randomized or structured search, seeking places where the field achieves or exceeds the prescribed threshold. Once a threshold point is reached, the ¿exploitation¿ component is initialized and the agents deploy so as to rapidly map the evolving isoline associated with the given value of the field. Conservative strategies will emphasize refining the detailed knowledge of the field in a small neighborhood of the isoline, while aggressive strategies will emphasize wide-ranging exploration of neighboring territory. The main decision problem under study involves finding the optimally aggressive exploration strategy. Additionally, the problem of the allocation of the agents between ¿exploration¿ and ¿exploitation¿ is considered. A performance metric is developed to compare the proposed methods with standard approaches such as random search and distributed raster scans.