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A Storm is Coming: A Modern Probabilistic Model Checker
TLDR
The new probabilistic model checker Storm features the analysis of discrete- and continuous-time variants of both Markov chains and MDPs and offers a Python API for rapid prototyping by encapsulating Storm’s fast and scalable algorithms.
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PROPhESY: A PRObabilistic ParamEter SYnthesis Tool
TLDR
ProPhESY, a tool for analyzing parametric Markov chains (MCs), can compute a rational function (i.e., a fraction of two polynomials in the model parameters) for reachability and expected reward objectives and supports the novel feature of conditional probabilities.
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SMT-RAT: An Open Source C++ Toolbox for Strategic and Parallel SMT Solving
TLDR
During the last decade, popular SMT solvers have been extended step-by-step with a wide range of decision procedures for different theories, but configuring solvers this way is a tedious task with restricted options.
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JANI: Quantitative Model and Tool Interaction
TLDR
The Jani model format and tool interaction protocol is a metamodel based on networks of communicating automata and has been designed for ease of implementation without sacrificing readability, to provide a stable and uniform interface between tools such as model checkers, transformers, and user interfaces.
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The Probabilistic Model Checker Storm
TLDR
The main features of Storm are reported and how to effectively use them are explained and an empirical evaluation of different configurations of Storm on the QComp 2019 benchmark set is presented.
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Parameter Synthesis for Markov Models: Faster Than Ever
TLDR
The technique provides the first sound and feasible method for performing parameter synthesis of Markov decision processes and outperforms the existing analysis of parametric Markov chains by several orders of magnitude regarding both run-time and scalability.
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Model-Based Safety Analysis for Vehicle Guidance Systems
TLDR
The proposed approach constructs dynamic fault trees (DFTs) to model a variety of safety concepts and E/E architectures for drive automation to evaluate various quantitative measures by means of model checking.
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Fast Dynamic Fault Tree Analysis by Model Checking Techniques
This paper presents a new state-space generation approach for dynamic fault trees (DFTs) that exploits several successful reduction techniques from the field of model checking. The key idea is to…
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Safety-Constrained Reinforcement Learning for MDPs
TLDR
This work abstracts controller synthesis for stochastic and partially unknown environments in which safety is essential as a Markov decision process in which the expected performance is measured using a cost function that is unknown prior to run-time exploration of the state space.
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Shielded Decision-Making in MDPs
TLDR
This work presents the concept of a shield that forces decision-making to provably adhere to safety requirements with high probability, and presents a method to compute probabilities of decision making regarding temporal logic constraints.
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