4 research outputs found

    Verification and control of partially observable probabilistic systems

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    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 states are partially visible to an observer or controller. We give probabilistic temporal logics that can express a range of quantitative properties of these models, relating to the probability of an event’s occurrence or the expected value of a reward measure. We then propose techniques to either verify that such a property holds or synthesise a controller for the model which makes it true. Our approach is based on a grid-based abstraction of the uncountable belief space induced by partial observability and, for dense-time models, an integer discretisation of real-time behaviour. The former is necessarily approximate since the underlying problem is undecidable, however we show how both lower and upper bounds on numerical results can be generated. We illustrate the effectiveness of the approach by implementing it in the PRISM model checker and applying it to several case studies from the domains of task and network scheduling, computer security and planning

    Checking Timed Büchi Automata Emptiness Efficiently

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    Abstract. This paper presents an on-the-fly and symbolic technique for efficiently checking timed automata emptiness. It is symbolic because it uses the simulation graph (instead of the region graph). It is on-the-fly because the simulation graph is generated during the test for emptiness. We have implemented a verification tool called PROFOUNDER based on this technique. To our knowledge, PROFOUNDER is the only available tool for checking emptiness of timed Büchi automata. To illustrate the practical interest of our approach, we show the performances of the tool on a non-trivial case study
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