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Robust Dynamic Programming for Temporal Logic Control of Stochastic Systems
[article]
2018
arXiv
pre-print
Discrete-time stochastic systems are an essential modelling tool for many engineering systems. We consider stochastic control systems that are evolving over continuous spaces. For this class of models, methods for the formal verification and synthesis of control strategies are computationally hard and generally rely on the use of approximate abstractions. Building on approximate abstractions, we compute control strategies with lower- and upper-bounds for satisfying unbounded temporal logic
arXiv:1811.11445v1
fatcat:zzkwsdnbqrbzpfqneafydnjlta