Research on Tactical Intention Recognition Method Based on Probabilistic Network Ontology Language
Zhen Lei, Peizhi Cui, Yanyan Huang · 2020
According to the characteristics of uncertainty, coordination and distribution in tactical intention recognition, this paper proposes a process of tactical intention recognition oriented to intelligent command and control decision support, which combines the perceptual ability of deep learning, the decision ability of reinforcement learning and the reasoning ability of multi-entity Bayesian network, with complementary advantages. At the same time, in order to realize the exchange, sharing and reuse of information, improve the representation and reasoning ability of traditional Bayesian network for the uncertainty in the field of tactical intention recognition, a method of tactical intention recognition based on probabilistic network ontology language is proposed. Simulation results verify the effectiveness and feasibility of the method.