一种新颖的抽象引导仿真方法,使用后验概率进行验证

Jian Wang, Huawei Li, Xiaowei Li
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引用次数: 0

摘要

本文提出了一种新的多目标状态抽象引导仿真方法,该方法利用抽象模型中状态的后验概率来代替以往抽象引导方法所使用的抽象距离作为仿真的指导。后验概率携带了抽象模型更精确的信息,能够提供更有效的指导,并允许仿真同时处理多个目标状态。实验结果表明,基于后验概率的仿真比基于抽象距离的仿真效率更高,多目标状态仿真框架有效地缩短了仿真周期。
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A novel abstraction-guided simulation approach using posterior probabilities for verification
This paper presents a novel abstraction-guided simulation approach for multiple target states which uses posterior probabilities of the states from the abstract model, instead of abstract distances used by former abstraction-guided approaches, as the guidance of simulation. The posterior probabilities carry more precise information of the abstract model, being able to offer more effective guidance as well as allow the simulation to deal with multiple target states at a time. Experimental results show that the simulation using posterior probabilities as guidance is much more efficient than that using the abstract distances, and the multiple target states simulation framework reduces the simulation cycles effectively.
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