Author: Ernst-Erich Doberkat Publisher: Springer ISBN: Category : Mathematics Languages : en Pages : 1102
Book Description
Provides a general mathematical framework for the analytical aspects of stochastic automata. Shows that under certain topological conditions, non-deterministic automata are generated, which in some cases are produced by stochastic automata.
Author: M.A.L. Thathachar Publisher: Springer Science & Business Media ISBN: 1441990526 Category : Science Languages : en Pages : 275
Book Description
Networks of Learning Automata: Techniques for Online Stochastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures from simple building blocks and uses stochastic algorithms for refining probabilities of selecting actions. Mathematical analysis of the behavior of games and feedforward networks is provided. Algorithms considered here can be used for online optimization of systems based on noisy measurements of performance index. Also, algorithms that assure convergence to the global optimum are presented. Parallel operation of automata systems for improving speed of convergence is described. The authors also include extensive discussion of how learning automata solutions can be constructed in a variety of applications.
Author: Pedro U. Lima Publisher: World Scientific ISBN: 9789810222550 Category : Computers Languages : en Pages : 172
Book Description
In recent years works done by most researchers towards building autonomous intelligent controllers frequently mention the need for a methodology of design and a measure of how successful the final result is. This monograph introduces a design methodology for intelligent controllers based on the analytic theory of intelligent machines introduced by Saridis in the 1970s. The methodology relies on the existing knowledge about designing the different sub-systems composing an intelligent machine. Its goal is to provide a performance measure applicable to any of the sub-systems, and use that measure to learn on-line the best among the set of pre-designed alternatives, given the state of the environment where the machine operates. Different designs can be compared using this novel approach.
Author: Jochen Schröder Publisher: Springer Science & Business Media ISBN: 3540440755 Category : Technology & Engineering Languages : en Pages : 355
Book Description
Ongoing advances in science and engineering enable mankind to design and operate increasingly sophisticated systems. Both their design and operation require the understanding of the system and its interaction with the envir- ment. This necessitates the formalisation of the knowledge about the system by models. A major issue is what kind of model is best suited for a given task. This book is about the supervision of continuous dynamical systems. Such systems are typically described by di?erential equations. However, this does notautomaticallymeanthatdi?erentialequationsarepropermodelsforso- ing supervision tasks. Instead, this book and recent approaches in literature show that supervision tasks do in general not require the use of such precise modelsasdi?erentialequations.Thisisofinterestbecauseuncertainties,t- ically occurring in supervision, make the use of precise models very di?cult. Alternative approaches therefore use less precise models such as discrete– event descriptions to solve supervision tasks on a higher level of abstraction. Discrete–event descriptions in form of automata are one of the key elements of this book. To reach this higher level of abstraction, uncertainties by qu- tisation are introduced on purpose, taking into account a loss of precision. This is one of the main di?erence to other approaches. When using nume- calmodelsliketransferfunctionsordi?erentialequations,uncertaintiesmake the analysis more di?cult. Not so here, where the system is described on a qualitative level on which uncertainties are naturally incorporated. The book presents a new way to describe systems for supervision. Preparing this book I learned that the key to solve supervision problems is simplicity.
Author: Azaria Paz Publisher: Academic Press ISBN: 1483268578 Category : Mathematics Languages : en Pages : 255
Book Description
Introduction to Probabilistic Automata deals with stochastic sequential machines, Markov chains, events, languages, acceptors, and applications. The book describes mathematical models of stochastic sequential machines (SSMs), stochastic input-output relations, and their representation by SSMs. The text also investigates decision problems and minimization-of-states problems arising from concepts of equivalence and coverings for SSMs. The book presents the theory of nonhomogeneous Markov chains and systems in mathematical terms, particularly in relation to asymptotic behavior, composition (direct sum or product), and decomposition. "Word functions," induced by Markov chains and valued Markov systems, involve characterization, equivalence, and representability by an underlying Markov chain or system. The text also discusses the closure properties of probabilistic languages, events and their relation to regular events, particularly with reference to definite, quasidefinite, and exclusive events. Probabilistic automata theory has applications in information theory, control, learning theory, pattern recognition, and time sharing in computer programming. Programmers, computer engineers, computer instructors, and students of computer science will find the collection highly valuable.
Author: A.S. Poznyak Publisher: Springer ISBN: 9783662174876 Category : Technology & Engineering Languages : en Pages : 207
Book Description
In the last decade there has been a steadily growing need for and interest in computational methods for solving stochastic optimization problems with or wihout constraints. Optimization techniques have been gaining greater acceptance in many industrial applications, and learning systems have made a significant impact on engineering problems in many areas, including modelling, control, optimization, pattern recognition, signal processing and diagnosis. Learning automata have an advantage over other methods in being applicable across a wide range of functions. Featuring new and efficient learning techniques for stochastic optimization, and with examples illustrating the practical application of these techniques, this volume will be of benefit to practicing control engineers and to graduate students taking courses in optimization, control theory or statistics.
Author: Kumpati S. Narendra Publisher: Courier Corporation ISBN: 0486268462 Category : Technology & Engineering Languages : en Pages : 498
Book 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.
Author: Arto Salomaa Publisher: Elsevier ISBN: 1483154394 Category : Reference Languages : en Pages : 277
Book Description
Theory of Automata deals with mathematical aspects of the theory of automata theory, with emphasis on the finite deterministic automaton as the basic model. All other models, such as finite non-deterministic and probabilistic automata as well as pushdown and linear bounded automata, are treated as generalizations of this basic model. The formalism chosen to describe finite deterministic automata is that of regular expressions. A detailed exposition regarding this formalism is presented by considering the algebra of regular expressions. This volume is comprised of four chapters and begins with a discussion on finite deterministic automata, paying particular attention to regular and finite languages; analysis and synthesis theorems; equivalence relations induced by languages; sequential machines; sequential functions and relations; definite languages and non-initial automata; and two-way automata. The next chapter describes finite non-deterministic and probabilistic automata and covers theorems concerning stochastic languages; non-regular stochastic languages; and probabilistic sequential machines. The book then introduces the reader to the algebra of regular expressions before concluding with a chapter on formal languages and generalized automata. Theoretical exercises are included, along with ""problems"" at the end of some sections. This monograph will be a useful resource for beginning graduate or advanced undergraduates of mathematics.
Author: Ernst-Erich Doberkat
Author: William J. Stewart
Author: M.A.L. Thathachar
Author: Pedro U. Lima
Author: Jochen Schröder
Author: Azaria Paz
Author: Aivar Arvidovich Lorents
Author: A.S. Poznyak
Author: Kumpati S. Narendra
Author: Arto Salomaa