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cs.FL2026
Path Abstraction for Markov Reward Models
Arnd Hartmanns, Robert Modderman
Path abstraction originated as a technique for counterexample refinement in probabilistic model checking. Given a discrete-time Markov chain, it summarises the probabilities passin…
cs.FL2025
DTMC Model Checking by Path Abstraction Revisited (extended version)
Arnd Hartmanns, Robert Modderman
Computing the probability of reaching a set of goal states G in a discrete-time Markov chain (DTMC) is a core task of probabilistic model checking. We can do so by directly computi…
cs.FL2024
Digging for Decision Trees: A Case Study in Strategy Sampling and Learning
Carlos E. Budde, Pedro R. D'Argenio, Arnd Hartmanns
We introduce a formal model of transportation in an open-pit mine for the purpose of optimising the mine's operations. The model is a network of Markov automata (MA); the optimisat…