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cs.LO2026
Shields to Guarantee Probabilistic Safety in MDPs
Linus Heck, Filip Macák, Roman Andriushchenko +2
Shielding is a prominent model-based technique to ensure safety of autonomous agents. Classical shielding aims to ensure that nothing bad ever happens and comes with strong guarant…
cs.LO2025
Constrained and Robust Policy Synthesis with Satisfiability-Modulo-Probabilistic-Model-Checking
Linus Heck, Filip Macák, Milan ÄeÅ¡ka +1
The ability to compute reward-optimal policies for given and known finite Markov decision processes (MDPs) underpins a variety of applications across planning, controller synthesis…
cs.LO2025
Generalized Parameter Lifting: Finer Abstractions for Parametric Markov Chains
Linus Heck, Tim Quatmann, Jip Spel +2
Parametric Markov chains (pMCs) are Markov chains (MCs) with symbolic probabilities. A pMC encodes a family of MCs, where each member is obtained by replacing parameters with const…