Index allocation method for unmanned swarm confrontation evaluation based on causal entropy
In response to the problem of index confusion and false correlation in traditional unmanned swarm confrontation evaluation index allocation methods,which can only select indexes with good correlation,causal entropy is innovatively is proposed to measure the certainty degree between the evaluation indexes and the effect of the confrontation task,in order to filter out the confusion among evaluation indexes.Taking the unmanned swarm air-ground collaborative encirclement test in the simulation environment as an example,the evaluation indexes that better reflect the combat capability of the unmanned swarm which are relatively independent are selected and optimized through causal allocation and reduction.The simulation results show that the proposed method can effectively optimize the evaluation index system,obtain more representative evaluation indicators,and has a certain degree of universality.
NETL
NSTL
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