LAUSR

Abstract We consider a scenario where a mobile agent is required to collect measurements from a geographically dispersed set of sensors and return them to a base. The agent faces a risk of destruction while traversing the environment to reach the sensors, and gets the reward for gathering a sensor measurement only if it successfully returns to base. We characterize several properties of the optimal policy for the agent based on a quantity that we term the "reward-to-risk" ratio of the tasks. We provide the optimal policy when the risk of destruction is sufficiently high, and evaluate several heuristic policies via simulation.