Abstract: Stochastic learning automata represent control mechanisms which adapt to changes in their environment, based on a learning process. Reinforcement schemes generate the learning behavior of stochastic learning automata. The importance of stochastic learning automata is given by their great number of applications. The aim of this talk is to make an introduction in stochastic learning automata and to present many new reinforcement schemes. Experimental results prove superior performances for the new schemes we built. The new reinforcement schemes were used for developing a simulator for an Intelligent Vehicle Control System, in a multi-agent approach.

Brief Biography of the Speaker:
Dana Simian received the diploma. in engineering from the University of Sibiu, Romania, the diploma. in Mathematics - Informatics from the University Babes-Bolyai of Cluj-Napoca, Romania and the Ph.D. from Babes-Bolyai University of Cluj- Napoca, Romania. She graduated many courses in Computer Science. She is the head of the Department of Computer Science from the Faculty of Sciences, University Lucian Blaga of Sibiu, Romania. She has a great experience in algorithms and numerical methods for modelling and optimization. She published 16 books, more than 60 articles and participated in the editorial board of more than 22 scientific publications (proceedings of international conferences).
She organized 7 special sessions within WSEAS conferences, 2 international workshops and an international conference on topics related to algorithms and computational techniques in modeling, approximation and optimization. She was a member of many scientific committees of international conferences. She was plenary speakers in 6 international conferences. She is reviewer of many scientific publications. She was involved as director of many research grants. She has been included in "Who is Who in the World" in 2006-2009 and in the "IBC Foremost Engineers of the World", 2008.