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Learning Automata: An Introduction (Dover Books on Electrical Engineering)
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About Learning Automata: An Introduction
Product Description This self-contained introductory text on the behavior of learning automata focuses on how a sequential decision-maker with a finite number of choices responds in a random environment. Topics include fixed structure automata, variable structure stochastic automata, convergence, 0 and S models, nonstationary environments, interconnected automata and games, and applications of learning automata. A must for all students of stochastic algorithms, this treatment is the work of two well-known scientists and is suitable for a one-semester graduate course in automata theory and stochastic algorithms. This volume also provides a fine guide for independent study and a reference for students and professionals in operations research, computer science, artificial intelligence, and robotics. The authors have provided a new preface for this edition. About the Author American control theorist Kumpati S. Narendra currently holds the Harold W. Cheel Professorship of Electrical Engineering at Yale University. Mandayam A. L. Thathachar is a professor at the Indian Institute of Science in Bangalore, India.
