Automata-theoretic models have been used successfully in modelbased process supervision and diagnosis. From a practical viewpoint, their main drawback is their complexity, which increases fast with the size of the original discrete-event system. This complexity can be reduced by compositional modelling resulting in an automata network. The reduced complexity of the network leads to a complexity...

This paper revisits the notions of observer and diagnoser, and adapts them to probabilistic automata, in a setting of weighted automata computations. In the non stochastic case, observers and diagnosers are obtained by standard elementary steps, as state augmentation, epsilon-reduction and determinization. It is shown that these steps can be adapted to probabilistic automata, and algorithms to ...

There is evidence that biological systems, such as the brain, work at a critical regime robust to noise, and are therefore able remain in it under perturbations. In this work, we address question of robustness systems noise. particular, investigate stochastic cellular automata (CAs) criticality. A CA one simplest models showing The transition state defined through set probabilities. We systemat...

We make the first steps towards showing a general “randomness for free” theorem for stochastic automata. The goal of such theorems is to replace randomized schedulers by averages of pure schedulers. Here, we explore the case of measurable multifunctions and their measurable selections. This involves constructing probability measures on the measurable space of measurable selections of a given me...

Like any software, web service fault management is also required to go through different phases of fault management lifecycle. Model based diagnosis has been a well established practice for its several positive aspects including cognitively being better understood by development and testing teams. Automata is a simple and formally well defined model being used for monitoring and diagnosis of sy...

We recently introduced p-automata, automata that read discrete-time Markov chains and showed they provide an automata-theoretic framework for reasoning about pCTL model checking and abstraction of discrete time Markov chains. We used turn-based stochastic parity games to define acceptance of Markov chains by a special subclass of p-automata. Definition of acceptance required a reduction to a se...