In this master thesis we investigate to infer models of standard communication protocols using automata learning techniques. One obstacle is that automata learning has been developed for machines with relatively small alphabets and a moderate number of states, whereas communication protocols usually have huge (practically infinite) sets of messages and sets of states. We propose to overcome thi...

in this paper, intelligent algorithm of ALATO based on Learning Automata using Adaptive Stochastic Petri Net presented to optimize the time in Economical Grid. Adaptive Stochastic Petri nets based on learning automata predicts the following optimized state through getting information from former system states and dynamic environmental reactions, makes the system current states appeared based on...

Abstract_Recent advances in wireless technology have enabled the rapid development of wireless manet networks. This paper proposes a novel on-demand routing protocol for mobile ad hoc networks based on best route selection with learning automata. Our proposed protocol is capable of operating efficiently in the route with considerationenergy restriction.We applied our method in an optimized vers...

A number of routing algorithms based on learning automata technique have been proposed for communication networks. How ever, there has been little work on the effects of variation of graph scarcity on the performance of these algorithms. In this paper, a comprehensive study is launched to investigate the performance of LASPA, the first learning automata based solution to the dynamic shortest pa...

In adaptive resonance theory network, the choice of vigilance factor (VF) and choice parameter. (CP) affects the performance of the network, such as the number of classes into which the data are classified. These parameters are typically chosen and adapted using human judgment, experience, and heuristic rules. Rather than choosing and optimizing these parameters manually, we use learning automa...

A stochastic automaton can perform a finite number of actions in a random environment. When a specific action is performed, the environment responds by producing an environment output that is stochastically related to the action. This response may be favourable or unfavourable. The aim is to design an automaton that can determine the best action guided by past actions and responses. Using Stoch...

An ad-hoc Learning Automata-based protocol for wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by means of Learning Automata. The Learning Automaton takes into account the network feedback information in order to update the choice probability ...