On Compositionality, Efficiency, and Applicability of Abstraction in Probabilistic Systems

DOI10.1007/978-3-540-95891-8_10zbMath1206.68207OpenAlexW2126092129MaRDI QIDQ3599065

Sonja Georgievska, Suzana Andova

Publication date: 3 February 2009

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-95891-8_10

Mathematics Subject Classification ID

Models and methods for concurrent and distributed computing (process algebras, bisimulation, transition nets, etc.) (68Q85) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (4)

Are Two Binary Operators Necessary to Obtain a Finite Axiomatisation of Parallel Composition? ⋮ On Compositionality, Efficiency, and Applicability of Abstraction in Probabilistic Systems ⋮ Monads and Quantitative Equational Theories for Nondeterminism and Probability ⋮ Branching bisimulation congruence for probabilistic systems

Cites Work

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• Refinement-oriented probability for CSP
• Comparative branching-time semantics for Markov chains
• Branching bisimulation for probabilistic systems: characteristics and decidability
• Model checking of probabilistic and nondeterministic systems
• Equational Axioms for Probabilistic Bisimilarity
• On Compositionality, Efficiency, and Applicability of Abstraction in Probabilistic Systems
• Process Algebra
• Three logics for branching bisimulation
• Branching time and abstraction in bisimulation semantics
• Validation of Stochastic Systems
• Branching Bisimulation Congruence for Probabilistic Systems
• A Complete Axiomatisation of Branching Bisimulation for Probabilistic Systems with an Application in Protocol Verification
• CONCUR 2005 – Concurrency Theory
• Processes, Terms and Cycles: Steps on the Road to Infinity

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