Quantitative Approximation of the Probability Distribution of a Markov Process by Formal Abstractions

DOI10.2168/LMCS-11(3:8)2015zbMath1342.60120arXiv1504.00039OpenAlexW1956206657MaRDI QIDQ3196339

Alessandro Abate, Sadegh Esmaeil Zadeh Soudjani

Publication date: 29 October 2015

Published in: Logical Methods in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1504.00039

zbMATH Keywords

Markov processesprobability distributionsdiscrete-time stochastic systemsformal abstractions

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Central limit and other weak theorems (60F05) Discrete-time Markov processes on general state spaces (60J05) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (7)

Formal abstraction and synthesis of parametric stochastic processes ⋮ Model-Based Formal Reliability Analysis of Grid Dynamics with Solar Energy Sources ⋮ Compositional abstraction of large-scale stochastic systems: a relaxed dissipativity approach ⋮ Verification of General Markov Decision Processes by Approximate Similarity Relations and Policy Refinement ⋮ A unified framework for coordination of thermostatically controlled loads ⋮ Dynamic Bayesian networks for formal verification of structured stochastic processes ⋮ Automated verification and synthesis of stochastic hybrid systems: a survey

Uses Software

• PRISM
• MRMC
• MPT

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