In this paper, we propose a distributed learning automata-based algorithm to solve the multicast routing problem in wireless mobile ad-hoc networks. The proposed algorithm estimates the expected relative mobility of each host, by sampling its movement parameters in various epochs, to realistically predict its motion behavior, and takes advantage of the Steiner connected dominating set to form t...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

کچ ي هد دنب هعطق شور كي هلاقم نيا رد ي واصت ي گنر ر ي هقبط زا هدافتسا اب ريگداي ياتاموتا رب ينتبم يزاف هدننک يدنب م داهنشيپ يلولس ي ددرگ . نيا رد هقبط نيناوق و تيوضع عباوت يلولس ريگداي ياهاتاموتا زا يا هعومجم كمك هب هدننک يدنب يم ديلوت کيتاموتا روط هب يزاف دنوش . ا يلولس ريگداي ياتاموتا ز نِگمه ان مِاگمهان هب زاب نيرتهب نتفاي يارب يرازبا ناونع تسا هدش هدافتسا يزاف تيوضع عباوت راتخاس . رد اتاموت...

In this paper, we give an overview on some algorithms for learning automata. Starting with Biermann’s and Angluin’s algorithms, we describe some of the extensions catering for specialized or richer classes of automata. Furthermore, we survey their recent application to verification problems.

Learning Automata (LA) are adaptive decision making devices suited for operation in unknown environments [12]. Originally they were developed in the area of mathematical psychology and used for modeling observed behavior. In its current form, LA are closely related to Reinforcement Learning (RL) approaches and most popular in the area of engineering. LA combine fast and accurate convergence wit...

A new formulation of adaptive categorization game of ART-type networks is described in this papet Learning automata dynamics is introduced into adaptive categorization game in ART-type networks so that the vigilance parameters p are adjusted to give variable sized clusters. Moreovel; repeated game analysis is also conducted on the learning automata based adaptive categorization game to study th...

A key problem in multi-agent reinforcement learning remains dealing with the large state spaces typically associated with realistic distributed agent systems. As the state space grows, agent policies become more and more complex and learning slows. One possible solution for an agent to continue learning in these large-scale systems is to learn a policy which generalizes over states, rather than...

0957-4174/$ see front matter 2011 Elsevier Ltd. A doi:10.1016/j.eswa.2011.01.098 ⇑ Corresponding author. E-mail addresses: [email protected] (J. Akbari ac.ir (M.R. Meybodi). Vertex coloring problem is a combinatorial optimization problem in which a color is assigned to each vertex of the graph such that no two adjacent vertices have the same color. Cellular learning automata (CLA) is an e...

One of the most important issues in web mining is how to find out similarities between web pages. In this paper we propose a method based on distributed learning automata which take advantage of usage data to find out web pages similarities. The idea of the proposed method is that if different users request a couple of pages consistently together, then these pages are likely to correspond to th...