
A deep reinforcement learning-based approach is presented to solve the single vehicle persistent surveillance problem with fuel constraints, where the objective is to determine an optimal sequence of visits to targets that minimizes the maximum time elapsed between successive visits while ensuring the vehicle never runs out of fuel.


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deep-reinforcement-learning-approach-for-single-vehicle-persistent-surveillance-with-fuel-constraints


Deep Reinforcement Learning Approach for Single Vehicle Persistent Surveillance with Fuel Constraints
