Patent ID: 11887485
Assignee: SHANGHAI UNIVERSITY
Field: Control (Instruments)
Classification: CPC G  B | IPC B  G

Claim 3:
4. The control method of claim 1, wherein constructing the intruding target interception policy output model comprises:
determining a training sample of an ith unmanned surface vessel; wherein the training sample is a data set continuous in time; the data set comprises a plurality of sample sets; each sample set comprises a plurality of elements, which are respectively the process state information at the current moment, an execution action at the current moment, a reward at the current moment and process state information at the next moment;
constructing the multi-agent deep deterministic policy gradient network structure; and
inputting the training sample of the ith unmanned surface vessel into the multi-agent deep deterministic policy gradient network structure to train the multi-agent deep deterministic policy gradient network structure, so as to obtain the intruding target interception policy output model corresponding to the ith unmanned surface vessel, and thus obtain the intruding target interception policy output model corresponding to each unmanned surface vessel.