Learning automata are used at the source nodes of a multimedia network to dynamically control the externally arriving traffic to the network. A new fixed structure learning automaton algorithm is used to control the traffic. At every network source, each different traffic type (data, voice, video, e.t.c.) is controlled by a different learning automaton. Every learning automaton makes its decisi...

In this report, we analyze the collective behavior of learning automata which are used in a programming language under development that combines reinforcement learning and symbolic programming [2, 6]. Learning automata can automatically improve their behavior by using a response from a random stationary environment, but when connected with each other, their behavior becomes much complex and har...

Automata learning is a known technique to infer a finite state machine from a set of observations. In this paper, we revisit Angluin’s original algorithm from a categorical perspective. This abstract view on the main ingredients of the algorithm lays a uniform framework to derive algorithms for other types of automata. We show a straightforward generalization to Moore and Mealy machines, which ...

Analysis by reduction is a linguistically motivated method for checking correctness of a sentence. It can be modelled by restarting automata. In this paper we propose a method for learning of restarting automata which are strictly locally testable (SLT-R-automata). The method is based on the concept of identification in the limit from positive examples only. Also we characterize the class of la...