We present a generic algorithmic scheme for learning languages defined over large or infinite alphabets such as bounded subsets of N and R, or Boolean vectors of high dimension. These languages are accepted by deterministic symbolic automata that use predicates to label transitions, forming a finite partition of the alphabet for every state. Our learning algorithm, an adaptation of Angluin’s L∗...

We present a generic algorithmic scheme for learning languages defined over large or infinite alphabets such as bounded subsets of N and R, or Boolean vectors of high dimension. These languages are accepted by deterministic symbolic automata that use predicates to label transitions, forming a finite partition of the alphabet for every state. Our learning algorithm, an adaptation of Angluin’s L∗...

A Learning Automaton is an automaton that interacts with a random environment, having as its goal the task of learning the optimal action based on its acquired experience. Many learning automata have been proposed, with the class of Estimator Algorithms being among the fastest ones. Thathachar and Sastry [24], through the Pursuit Algorithm, introduced the concept of learning algorithms. Their a...

In this paper, we propose a novel algorithm to learn Büchi automaton from teacher who knows an ? -regular language. The learned can be nondeterministic or limit deterministic automaton. learning is based on formalism called family of DFAs (FDFAs) recently proposed by Angluin and Fisman. main catch that use classification tree structure instead the standard observation table structure. worst cas...

It is inevitable for networks to be invaded during operation. The intrusion tolerance technology comes into being enable provide the necessary network services. This paper introduces an automatic learning mechanism of system update security strategy, and derives finite automaton model from existing model. proposed was quantified by Markov theory compute stable probability each state. calculated...

We introduce a two generated weakly branch contracting automaton group $G$ which is generated by a two state automaton on a three letter alphabet. Using its branch structure and the finiteness nature of a sequence of its factor groups we compute the order of some of these factors. Furthermore some algebraic properties of $G$ are detected .

A DAPTIVE and learning systems have drawn considerable attention in the last few decades due to their inherent strength in suitably modeling many real-world complex systems , which are otherwise difficult to model using the traditional existing tools and systems. There exist many theories of adaptation and learning such as learning automata (LA), neural networks, and cellular automata. Consider...

In this note, we define the concepts of admissible relation and admissible partition for an arbitrary BL-general fuzzy automaton.In particular, a connection between the admissible partition and the quotient BL-general fuzzy automaton is presented.It is shown that if we use the maximal admissible partition, then we obtain a quotient BL-general fuzzy automaton and this quotient is minimal. Finall...

Particle swarm optimization (PSO) is a population based statistical optimization technique which is inspired by social behavior of bird flocking or fish schooling. The main weakness of PSO especially in multimodal problems is trapping in local minima. Recently a learning automata based PSO called PSO-LA to improve the performance of PSO has been reported. PSO-LA uses one learning automaton for ...