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Approximate Markovian abstractions for linear stochastic systems
2012
2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
In this paper, we present a method to generate a finite Markovian abstraction for a discrete time linear stochastic system evolving in a full dimensional polytope. Our approach involves an adaptation of an existing approximate abstraction procedure combined with a bisimulation-like refinement algorithm. It proceeds by approximating the transition probabilities from one region to another by calculating the probability from a single representative point in the first region. We derive the exact
doi:10.1109/cdc.2012.6426184
dblp:conf/cdc/LahijanianAB12
fatcat:534u4ikrybdandf654bon2frpy