Abstract
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 bound of the approximation error and an explicit expression for its growth over time. To achieve a desired error value, we employ an adaptive refinement algorithm that takes advantage of the dynamics of the system. We demonstrate the performance of our method through simulations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
