Verification of General Markov Decision Processes by Approximate Similarity Relations and Policy Refinement
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Publication:5348126
DOI10.1137/16M1079397zbMath1367.93615MaRDI QIDQ5348126
Sadegh Esmaeil Zadeh Soudjani, Alessandro Abate, Sofie Haesaert
Publication date: 14 August 2017
Published in: SIAM Journal on Control and Optimization (Search for Journal in Brave)
Discrete-time control/observation systems (93C55) Synthesis problems (93B50) Markov and semi-Markov decision processes (90C40) Specification and verification (program logics, model checking, etc.) (68Q60) Stochastic systems in control theory (general) (93E03)
Related Items (11)
Robust Control for Dynamical Systems with Non-Gaussian Noise via Formal Abstractions ⋮ Similarity quantification for linear stochastic systems: a coupling compensator approach ⋮ Compositional abstraction of large-scale stochastic systems: a relaxed dissipativity approach ⋮ Certified reinforcement learning with logic guidance ⋮ SySCoRe: Synthesis via Stochastic Coupling Relations ⋮ Compositional abstraction-based synthesis for continuous-time stochastic hybrid systems ⋮ Compositional construction of infinite abstractions for networks of stochastic control systems ⋮ Compositional abstraction-based synthesis of general MDPs via approximate probabilistic relations ⋮ Safe-visor architecture for sandboxing (AI-based) unverified controllers in stochastic cyber-physical systems ⋮ Automated verification and synthesis of stochastic hybrid systems: a survey ⋮ Automata-based controller synthesis for stochastic systems: a game framework via approximate probabilistic relations
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Cites Work
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- Approximation metrics based on probabilistic bisimulations for general state-space Markov processes: a survey
- Metrics for labelled Markov processes
- Markov chains and stochastic stability
- Hierarchical control system design using approximate simulation
- Stochastic optimal control. The discrete time case
- Bisimulation through probabilistic testing
- Approximating labelled Markov processes
- Verification of general Markov decision processes by approximate similarity relations and policy refinement
- The existence of probability measures with given marginals
- Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems
- On the effect of perturbation of conditional probabilities in total variation
- Bisimulation for labelled Markov processes
- Adaptive and Sequential Gridding Procedures for the Abstraction and Verification of Stochastic Processes
- Symbolic Control of Stochastic Systems via Approximately Bisimilar Finite Abstractions
- Robust PCTL model checking
- On Probabilistic Alternating Simulations
- Quantitative Approximation of the Probability Distribution of a Markov Process by Formal Abstractions
- Verification and Control of Hybrid Systems
- Semi-pullbacks and bisimulation in categories of Markov processes
- Average Optimality in Markov Control Processes via Discounted-Cost Problems and Linear Programming
- Approximations of Stochastic Hybrid Systems
- Probabilistic Model Checking of Labelled Markov Processes via Finite Approximate Bisimulations
- The Existence of Probability Measures with Given Marginals
- Hybrid Systems: Computation and Control
- Hybrid Systems: Computation and Control
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