Are Parametric Markov Chains Monotonic?
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Abstract (arXiv)
This paper presents a simple algorithm to check whether reachability probabilities in parametric Markov chains are monotonic in (some of) the parameters. The idea is to construct - only using the graph structure of the Markov chain and local transition probabilities - a pre-order on the states. Our algorithm cheaply checks a sufficient condition for monotonicity. Experiments show that monotonicity in several benchmarks is automatically detected, and monotonicity can speed up parameter synthesis up to orders of magnitude faster than a symbolic baseline.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 2; 2024: 0; 2025: 2.
6 papers.
- 2021Convex Optimization for Parameter Synthesis in MDPscited by 8
- 2021Fine-Tuning the Odds in Bayesian Networkscited by 3
- 2023Graph-Based Reductions for Parametric and Weighted MDPscited by 2
- 2025Best-Effort Policies for Robust Markov Decision Processescited by 1
- 2023Finding an ε-close Variation of Parameters in Bayesian Networkscited by 0
- 2025Analyzing Value Functions of States in Parametric Markov Chainscited by 0
- 2025Best-Effort Policies for Robust Markov Decision Processes11 Aug 2025
- 2025Analyzing Value Functions of States in Parametric Markov Chains23 Apr 2025
- 2023Finding an ε-close Variation of Parameters in Bayesian Networks17 May 2023
- 2023Graph-Based Reductions for Parametric and Weighted MDPs9 May 2023
- 2021Convex Optimization for Parameter Synthesis in MDPs30 Jun 2021
- 2021Fine-Tuning the Odds in Bayesian Networks29 May 2021