The models were simulated using MatLAB modules Simulink and Reinforcement Learning Toolbox on a 12x2 grid. The model was trained for 1000 epochs. A sample output is displayed on the right side.

Reward Values

• +1 for moving to a previously unexplored cell (white).

• +2 for moving closer to the destination

• +0.01 for getting closer to aerial base station

• +0.01 for getting closer to aerial base station

• -2 for moving farther from destination

• -0.01 for moving farther from monitoring drones

• -2 for an illegal actions

• -0.05 for an action that results in movement (movement cost).

• -0.1 for an action that results in no motion (lazy penalty).

• -0.1 multiplied by number of previous visits for moving to a previously explored cell