We investigate the relations between two automata-based models for describing and studying distributed services, called contract automata and communicating machines. In the first model, distributed services are abstracted away as automata oblivious of their partners that coordinate with each other through an orchestrator. The second one is concerned with the interactions occurring between distr...

This paper presents one-stack automata as acceptors of context-free languages; these are equivalent to Pushdown Automata which are well known in automata theory. As equivalence relations such as equivalence of Turing Machines and two-stack Pushdown Automata help in learning general properties of formal modeling, the equivalence relation of Pushdown Automata and one-stack automata also helps in ...

Abstract AALpy is an extensible open-source Python library providing efficient implementations of active automata learning algorithms for deterministic, non-deterministic, and stochastic systems. We put a special focus on the conformance testing aspect in learning, as well intuitive seamlessly integrated interface characterizing real-world reactive In this article, we present ’s core functional...

In the past decade, active automata learning, an originally merely theoretical enterprise, got attention as a method for dealing with black-box or third party systems. Applications ranged from the support of formal verification, e.g. for assume guarantee reasoning [4], to usage of learned models as the basis for regression testing. In the meantime, a number of approaches exploiting active learn...

In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary model. In this model, every genome in the population is assigned to one cell of CLA and each cell in CLA is equipped with a set of learning automata. Actions selected by learning automata of a cell determine the genome...

We have trained networks of E II units with short-range connections to simulate simple cellular automata that exhibit complex or chaotic behaviour. Three levels of learning are possible (in decreasing order of difficulty): learning the underlying automaton rule, learning asymptotic dynamical behaviour, and learning to extrapolate the training history. The levels of learning achieved with and wi...

Adding cognition to the existing Wireless Sensor Networks (WSNs) with a cognitive networking approach brings about many benefits. Cognitive networking deals with using cognition to the entire network protocol stack to achieve stack-wide as well as network-wide performance goals; unlike cognitive radios that apply cognition only at the physical layer to overcome the problem of spectrum scarcity....

In this paper, the concepts of somewhat fuzzy automata continuous functions and somewhat fuzzy automata open functions in fuzzy automata topological spaces are introduced and some interesting properties of these functions are studied. In this connection, the concepts of fuzzy automata resolvable spaces and fuzzy automata irresolvable spaces are also introduced and their properties are studied.