灰色博弈网决策模型研究

针对超博弈决策问题中存在的"灰色"的"贫信息"问题,提出一种基于信息缺失下的灰色博弈网模型;并给出了灰色博弈网的建模思路及其纳什均衡求解算法,解决了博弈网决策模型中的灰色不确定性问题。通过宏观信念建模,生成全局灰场景和优化典型灰场景。通过微观信念均衡建模,利用可能度分析和粒子群算法求解纳什均衡。最后实例仿真,验证了该灰色博弈网模型的可行性和有效性,真实性好,有较高的应用研究价值。

Decision-making Research of Gray Networkof Games

Aiming at super game problem that there may be the "gray" and "poor information" problem, puts forward a model based on grey network of games under the lack of information network, and puts forward the modeling ideas of grey network of games and its Nash equilibrium solution algorithm, and solved the grey uncertainty problems in network of games modeling. Through macroscopic faith modeling, generate global grey scene and typical optimization scene, through micro belief equilibrium modeling, using possible degree analysis and particle swarm optimization to solve the Nash equilibrium. Finally instance simulation to verify the feasibility and effectiveness of the grey game network algorithm, its authenticity is good, and there is a high application value.