By modeling the scenario of a hypothetical task and analyzing the uncertainty of probability information such as sensor detection,damage,and interference,a game decision-solving method for manned/unmanned platform collaborative tasks under uncertainty information is proposed.Based on the detection probability,information interfer-ence probability and weapon damage probability information of red and blue sensors,a cooperative task game Decision model is constructed.Combining the interval number sorting method and the quantum particle swarm optimization al-gorithm,the Nash equilibrium solution of the game problem of manned/unmanned platform collaborative task under uncertainty information is solved.Simulation studies have shown that the quantum particle swarm optimization algo-rithm is feasible and efficient in solving Nash equilibrium problems under the scenarios and constraints in this paper,providing a solution for collaborative task game decision-making problems in complex environments.
关键词
不确定性信息/有人/无人平台协同/博弈决策/量子粒子群/区间数排序
Key words
Uncertainty information/Manned/unmanned platform collaboration/Game decision-making/Quantum particle swarm/Interval number sorting
维普
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