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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, Q 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.Reprint of the Prentice-Hall, Inc, Englewood Cliffs, New Jersey, 1989 edition.
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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, Q 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.Reprint of the Prentice-Hall, Inc, Englewood Cliffs, New Jersey, 1989 edition.
