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.
This graduate-level text focuses on the stability of adaptive systems, and offers a thorough understanding of the global stability properties essential to designing adaptive systems. Its self-contained, unified presentation of well-known results establishes the close connections between seemingly independent developments in the field. Prerequisites include a knowledge of linear algebra and differential equations, as well as a familiarity with basic concepts in linear systems theory. The first chapter sets the tone for the entire book, introducing basic concepts and tracing the evolution of the field from the 1960s through the 1980s. The first seven chapters are accessible to beginners, and the final four chapters are geared toward more advanced, research-oriented students. Problems ranging in complexity from relatively easy to quite difficult appear throughout the text. Topics include results in stability theory that emphasize incidents directly relevant to the study of adaptive systems; the stability properties of adaptive observers and controllers; the important concept of persistent excitation; the use of error models in systems analysis; areas of intense research activity; and five detailed case studies of systems in which adaptive control has proved successful
This volume offers a glimpse of the status of research in adaptive and learning systems in 1985. In recent years these areas have spawned a multiplicity of ideas so rapidly that the average research worker or practicing engineer is overwhelmed by the flood of information. The Yale Workshop on Applications of Adaptive Systems Theory was organized in 1979 to provide a brief respite from this deluge, wherein critical issues may be examined in a calm and collegial environment. The fourth of the series having been held in May 1985, it has now become well established as a biennial forum for the lively exchange of ideas in the ever changing domain of adaptive systems. The scope of this book is broad and ranges from theoretical investigations to practical applications. It includes twenty eight papers by leaders in the field, selected from the Pro ceedings of the Fourth Yale Workshop and divided into five sections. I have provided a brief introduction to each section so that it can be read as a self-contained unit. The first section, devoted to adaptive control theory, suggests the intensity of activity in the field and reveals signs of convergence towards some common themes by workers with rather different moti vation. Preliminary results concerning the reduced order model problem are dramatically changing the way we view the field and bringing it closer to other areas such as robust linear control where major advances have been recently reported.
Frequency Domain Criteria for Absolute Stability presents some generalizations of the well-known Popov solution to the absolute stability problem proposed by Lur'e and Postnikov in 1944. This book is divided into nine chapters that focus on the application of Lyapunov's direct method to generate frequency domain criteria for stability. The first eight chapters explore the systems with a single nonlinear function or time-varying parameter. These chapters also discuss the development of stability criteria for these systems, the sufficiency theorems, and Lyapunov function. Some of the theorems applied to a damped version of the Mathieu equation and to a nonlinear equation derived from it are also covered. The concluding chapter deals with systems with multiple nonlinearities or time-varying gains. This chapter also outlines the basic definitions and tools, as well as the derivation of stability criteria. This work will serve as a reference for research courses concerning stability problems related to the absolute stability problem of Lur'e and Postnikov. Engineers and applied mathematicians will also find this book invaluable.
In September of 2022, India's GDP crossed that of Britain to make it the world's fifth largest economy. For a country that had been struggling with slow growth for decades, it was a significant moment. The tipping point-that moment when a process of change is initiated which will transform how we think, behave or live-came in the summer of 1991 under the leadership of someone considered the person least likely to launch such a change. The government of P.V. Narasimha Rao, who had just turned 70, announced a series of measures that have today placed India among the top economies. This was not all. The five years of his prime-ministership, from 1991 to 1996, were marked by several other changes whose impact continues to be felt. Alongside devastating events like the Babri Masjid demolition and tackling bitter politics in a divided Congress party. S. Narendra was a close associate through this period and sheds light on many key events and the internecine rivalries and politics that Rao had to counter to be able to function. He was a cog in the wheel of bigger things but perfectly placed to see what happened in the grey area between policy-making, administration and politics, and to explain, at least in part, the actions of the man at the centre of it all. This is a first-hand, indispensable account of history in the making.
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