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This work considers designing an unmanned target hunting system for a swarmof unmanned underwater vehicles (UUVs) to hunt a target with highmaneuverability. Differential game theory is used to analyze combat policies ofUUVs and the target within finite time. The challenge lies in UUVs must conducttheir control policies in consideration of not only the consistency of thehunting team but also escaping behaviors of the target. To obtain stablefeedback control policies satisfying Nash equilibrium, we construct theHamiltonian function with Leibniz's formula. For further taken underwaterdisturbances and communication delay into consideration, modified deepreinforcement learning (DRL) is provided to investigate the underwater targethunting task in an unknown dynamic environment. Simulations show thatunderwater disturbances have a large impact on the system consideringcommunication delay. Moreover, consistency tests show that UUVs perform betterconsistency with a relatively small range of disturbances.

Underwater Differential Game: Finite-Time Target Hunting Task with Communication Delay