Approximation metrics based on probabilistic bisimulations for general state-space Markov processes: a survey

DOI10.1016/j.entcs.2013.12.002zbMath1334.68128OpenAlexW2122994575WikidataQ113317934 ScholiaQ113317934MaRDI QIDQ271706

Alessandro Abate

Publication date: 19 April 2016

Full work available at URL: https://doi.org/10.1016/j.entcs.2013.12.002

zbMATH Keywords

Markov processesLyapunov theoryformal approximationsmetrics over probability measuresprobabilistic bisimulationsprobabilistic reachabilityrandomized methodsstochastic contractivity

Mathematics Subject Classification ID

Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Specification and verification (program logics, model checking, etc.) (68Q60) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (7)

Robust Control for Dynamical Systems with Non-Gaussian Noise via Formal Abstractions ⋮ Quantitative analysis of software approximate correctness ⋮ Verification of General Markov Decision Processes by Approximate Similarity Relations and Policy Refinement ⋮ On the Relationship Between Bisimulation and Trace Equivalence in an Approximate Probabilistic Context ⋮ A probabilistic calculus of cyber-physical systems ⋮ Compositional abstraction-based synthesis of general MDPs via approximate probabilistic relations ⋮ Automated verification and synthesis of stochastic hybrid systems: a survey

Uses Software

• HyTech

Cites Work

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