Описание: It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics.
Описание: It also explores approximations under convexity and a new trend in approximation theory - approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations.
Описание: This book focuses on computational and fractional analysis, two areas that are very important in their own right, and which are used in a broad variety of real-world applications. We also cover the conformable fractional approximation of Csiszar`s well-known f-divergence, and present conformable fractional self-adjoint operator inequalities.
Автор: Naci Saldi; Tam?s Linder; Serdar Y?ksel Название: Finite Approximations in Discrete-Time Stochastic Control ISBN: 3030077101 ISBN-13(EAN): 9783030077105 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems.
This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.
Описание: Preface.- Notations and Abbreviations.- Introduction and Motivating Examples.- Mathematical machinery.- Yosida Approximations of Stochastic Differential Equations.- Yosida Approximations of Stochastic Differential Equations with Jumps.- Applications to Stochastic Stability.- Applications to Stochastic Optimal Control.- Appendix A: Nuclear and Hilbert-Schmidt Operators.- Appendix B: Multivalued Maps.- Appendix C: Maximal Monotone Operators.- Appendix D: The Duality Mapping.- Appendix E: Random Multivalued Operators.- Bibliographical Notes and Remarks.- Bibliography.
Автор: Riccardo Zoppoli; Marcello Sanguineti; Giorgio Gne Название: Neural Approximations for Optimal Control and Decision ISBN: 3030296911 ISBN-13(EAN): 9783030296919 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Поставка под заказ.
Описание: Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.Features of the text include:• a general functional optimization framework;• thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;• comparison of classical and neural-network based methods of approximate solution;• bounds to the errors of approximate solutions;• solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several;• applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and• numerous, numerically detailed examples.The authors’ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.
Robots' Ethical Systems: From Asimov's Laws to Principlism, from Assistive Robots to Self-driving Cars.- Robot: Multi-use Tool and Ethical Agent.- Towards Human--Robot Interaction Ethics.- Shall I Show You Some Other Shirts Too? The Psychology and Ethics of Persuasive Robots.- Ethical Regulation of Robots Must Be Embedded in Their Operating Systems.- Non-monotonic Resolution of Conflicts for Ethical Reasoning.- Grafting Norms onto the BDI Agent Model.- Constrained Incrementalist Moral Decision Making for a Biologically Inspired Cognitive Architecture.- Case-Supported Principle-Based Behavior Paradigm.- The Potential of Logic Programming as a Computational Tool to Model Morality.
Описание: This research monograph brings together, for the first time, the varied literature on Yosida approximations of stochastic differential equations (SDEs) in infinite dimensions and their applications into a single cohesive work. The author provides a clear and systematic introduction to the Yosida approximation method and justifies its power by presenting its applications in some practical topics such as stochastic stability and stochastic optimal control. The theory assimilated spans more than 35 years of mathematics, but is developed slowly and methodically in digestible pieces.The book begins with a motivational chapter that introduces the reader to several different models that play recurring roles throughout the book as the theory is unfolded, and invites readers from different disciplines to see immediately that the effort required to work through the theory that follows is worthwhile. From there, the author presents the necessary prerequisite material, and then launches the reader into the main discussion of the monograph, namely, Yosida approximations of SDEs, Yosida approximations of SDEs with Poisson jumps, and their applications. Most of the results considered in the main chapters appear for the first time in a book form, and contain illustrative examples on stochastic partial differential equations. The key steps are included in all proofs, especially the various estimates, which help the reader to get a true feel for the theory of Yosida approximations and their use.This work is intended for researchers and graduate students in mathematics specializing in probability theory and will appeal to numerical analysts, engineers, physicists and practitioners in finance who want to apply the theory of stochastic evolution equations. Since the approach is based mainly in semigroup theory, it is amenable to a wide audience including non-specialists in stochastic processes.
Автор: Saldi, Naci. Название: Finite approximations in discrete-time stochastic control : ISBN: 3319790323 ISBN-13(EAN): 9783319790329 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems.
This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.
Автор: Bl. Sendov; Gerald Beer Название: Hausdorff Approximations ISBN: 9401067872 ISBN-13(EAN): 9789401067874 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Et moi, ..., si j'avait su comment en revenir, One service mathematics has rendered the je n'y serais point a1Ie.' human race. It has put common sense back Jules Verne where it belongs, on the topmost shelf next to the dusty canister labelled 'discarded non- The series is divergent; therefore we may be sense'. able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non- linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com- puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Описание: Preview of Predictor Feedback and Delay Compensation.- Part I: Linear Systems Under Predictor Feedback.- Linear Systems with State Measurement.- Linear Systems with Output Measurement.- Part II: Nonlinear Systems Under Predictor Feedback.- Nonlinear Systems with State Measurement.- Nonlinear Systems with Output Measurement.- Application to the Chemostat.- Part III: Extensions of Predictor Feedback.- Systems Described by Integral Delay Equations.- Discrete-Time Systems.
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