We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
We consider the equivalence problem for labeled Markov chains (LMCs), where each state is labeled with an observation. Two LMCs are equivalent if every finite sequence of observat...
Laurent Doyen, Thomas A. Henzinger, Jean-Fran&cced...
In [3] a probabilistic semantics for timed automata has been defined in order to rule out unlikely (sequences of) events. The qualitative model-checking problem for LTL propertie...
Nathalie Bertrand, Patricia Bouyer, Thomas Brihaye...
We aim at finding a set of timing parameters for which a given timed automaton has a “good” behavior. We present here a novel approach based on the decomposition of the parame...