Application of DDPG deep reinforcement learning algorithm in unmanned ship target tracking and rescue
In order to ensure the efficiency of maritime rescue activities,the ship tracking and rescue target algorithm from three aspects:state space,action space and reward function is designed and the unmanned ship tracking and rescue is applied.The results show that the stable success rate of ddpg algorithm is close to 100%and the performance is excellent.The cumulative reward value of the final round of the designed algorithm can be stable at about 10,while the average duration can be stable at about 80 s.It can adjust its movement strategy according to the state of the surrounding environment,meet the urgent requirements in maritime rescue activities,and provide a new idea for research in related fields.
NETL
NSTL
万方数据
