Rewarding probabilistic hybrid automata
Proceedings of the 16th international conference on Hybrid systems: computation and control
Compositional verification and optimization of interactive markov chains
CONCUR'13 Proceedings of the 24th international conference on Concurrency Theory
From software verification to `everyware' verification
Computer Science - Research and Development
Model checking for probabilistic timed automata
Formal Methods in System Design
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We consider a class of hybrid systems that involve random phenomena, in addition to discrete and continuous behaviour. Examples of such systems include wireless sensing and control applications. We propose and compare two abstraction techniques for this class of models, which yield lower and upper bounds on the optimal probability of reaching a particular class of states. We also demonstrate the applicability of these abstraction techniques to the computation of long-run average reward properties and the synthesis of controllers. The first of the two abstractions yields more precise information, while the second is easier to construct. For the latter, we demonstrate how existing solvers for hybrid systems can be leveraged to perform the computation.