All objects move towards the center at a constant speed.
Targets that are closer to the center provide proportionally greater reward, if found. However, non-targets trigger negative reward when located. Hence the system must try to maximize its total reward by locating optimal paths to the closest moving targets while reducing interaction with non-targets. The goal is for the system to explicitly explore its environment before converging to optimal paths towards maximal reward. Delayed reward suggests that the agent take into account the forthcoming state and immediate reward as the basis for selecting its current action.