Xueyi Zou

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We propose automated techniques for the verification and control of probabilistic real-time systems that are only partially observable. To formally model such systems, we define an extension of proba-bilistic timed automata in which local states are partially visible to an observer or controller. We give a probabilistic temporal logic that can express a(More)
We present automated techniques for the verification and control of partially observable, probabilistic systems for both discrete and dense models of time. For the discrete-time case, we formally model these systems using partially observable Markov decision processes; for dense time, we propose an extension of probabilistic timed automata in which local(More)
The development of the new generation of airborne collision avoidance system ACAS X adopts a model-based optimization approach, where the collision avoidance logic is automatically generated based on a probabilistic model and a set of preferences. It has the potential for safety benefits and shortening the development cycle, but it poses new challenges for(More)
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