As for such problems existing in the application of current agent technology in the field of military command and control as high demand for computational resources,sparse reward values,slow convergence speed,and poor reasoning effects,a command agent technology based on Spiking Neural Network(SNN)and hierarchical reinforcement learning is proposed.Firstly,the military comm-and agent is modeled based on the idea of hierarchical reinforcement learning,and the decision-making model of the agent is constructed with SNN.Then,the learning algorithm of ANN-SNN conversion is used to obtain the command agent based on SNN.Finally,a comparative experiment is carried out based on the"Mozi"wargaming software.Compared with the existing agent technology,the proposed method has lower demand for computational resources and higher win rate of game confrontation.
维普
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