Stochastic multiplicity automata (SMA) are weighted finite automata that generalize probabilistic automata. They have been used in the context of probabilistic grammatical inference. Observable operator models (OOMs) are a generalization of hidden Markov models, which in turn are models for discrete-valued stochastic processes and are used ubiquitously in the context of speech recognition and b...

A wide range of complex systems with local interactions could be described by cellular automata. Despite the fact, that in general, behaviour each automata on its own quite simple, their effective combination, or setting unusual interaction rules may result extraordinary system much more complicated behaviour, unexpected and ambiguous observation results. Stochasticity between cells approximate...

Stochastic automata are a formal compositional model for concurrent stochastic timed systems, with general distributions and nondeterministic choices. Measures of interest are defined over schedulers that resolve the nondeterminism. In this paper we investigate the power of various theoretically and practically motivated classes of schedulers, considering the classic complete-information view a...

We introduce a framework to study stochastic systems, i.e. systems in which the time of occurrence of activities is a general random variable. We introduce and discuss in depth a stochastic process algebra (named) adequate to specify and analyse those systems. In order to give semantics to , we also introduce a model that is an extension of traditional automata with clocks which are basically r...