iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
— We propose a new probabilistic temporal logic iLTL which captures properties of systems whose state can be represented by probability mass functions (pmf’s). Using iLTL, we c...
This paper considers QLtl, a quantitative analagon of Ltl and presents algorithms for model checking QLtl over quantitative versions of Kripke structures and Markov chains.
We present Hintikka games for formulae of the probabilistic temporal logic PCTL and countable labeled Markov chains as models, giving an operational account of the denotational se...
Harald Fecher, Michael Huth, Nir Piterman, Daniel ...
rexample Guided Abstraction-Refinement Framework for Markov Decision Processes ROHIT CHADHA and MAHESH VISWANATHAN Dept. of Computer Science, University of Illinois at Urbana-Champ...