Evolutionary Learning Algorithms for Neural Adaptive Control

Evolutionary Learning Algorithms for Neural Adaptive Control PDF Author: Dimitris C. Dracopoulos
Publisher: Springer
ISBN: 1447109031
Category : Computers
Languages : en
Pages : 214

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Book Description
Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.

Evolutionary Learning Algorithms for Neural Adaptive Control

Evolutionary Learning Algorithms for Neural Adaptive Control PDF Author: Dimitris Dracopoulos
Publisher:
ISBN: 9781447109044
Category :
Languages : en
Pages : 224

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Book Description


Biologically Inspired Networking and Sensing: Algorithms and Architectures

Biologically Inspired Networking and Sensing: Algorithms and Architectures PDF Author: Lio, Pietro
Publisher: IGI Global
ISBN: 1613500939
Category : Computers
Languages : en
Pages : 311

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Book Description
Biologically Inspired Networking and Sensing: Algorithms and Architectures offers current perspectives and trends in biologically inspired networking, exploring various approaches aimed at improving network paradigms. Research contained within this compendium of research papers and surveys introduces researches in the fields of communication networks, performance modeling, and distributed computing to new advances in networking.

Genetic Programming III

Genetic Programming III PDF Author: John R. Koza
Publisher: Morgan Kaufmann
ISBN: 9781558605435
Category : Computers
Languages : en
Pages : 1516

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Book Description
Genetic programming (GP) is a method for getting a computer to solve a problem by telling it what needs to be done instead of how to do it. Koza, Bennett, Andre, and Keane present genetically evolved solutions to dozens of problems of design, control, classification, system identification, and computational molecular biology. Among the solutions are 14 results competitive with human-produced results, including 10 rediscoveries of previously patented inventions.

Foundations of Trusted Autonomy

Foundations of Trusted Autonomy PDF Author: Hussein A. Abbass
Publisher: Springer
ISBN: 3319648160
Category : Technology & Engineering
Languages : en
Pages : 399

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Book Description
This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.

Connectionist Models of Learning, Development and Evolution

Connectionist Models of Learning, Development and Evolution PDF Author: Robert M. French
Publisher: Springer Science & Business Media
ISBN: 1447102819
Category : Psychology
Languages : en
Pages : 327

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Book Description
Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.

Adaptive Systems in Drug Design

Adaptive Systems in Drug Design PDF Author: Gisbert Schneider
Publisher: CRC Press
ISBN: 149871370X
Category : Science
Languages : en
Pages : 184

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Book Description
A brief history of drug design presented to make clear that there are fashions in this important field and that they change rather rapidly. This is due in part to the fact that the way that a new paradigm is accepted in a drug company often does not depend on its scientific merit alone.

Concepts for Neural Networks

Concepts for Neural Networks PDF Author: Lawrence J. Landau
Publisher: Springer Science & Business Media
ISBN: 1447134273
Category : Computers
Languages : en
Pages : 316

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Book Description
Concepts for Neural Networks - A Survey provides a wide-ranging survey of concepts relating to the study of neural networks. It includes chapters explaining the basics of both artificial neural networks and the mathematics of neural networks, as well as chapters covering the more philosophical background to the topic and consciousness. There is also significant emphasis on the practical use of the techniques described in the area of robotics. Containing contributions from some of the world's leading specialists in their fields (including Dr. Ton Coolen and Professor Igor Aleksander), this volume will provide the reader with a good, general introduction to the basic concepts needed to understan d and use neural network technology.

Intelligent Technologies and Techniques for Pervasive Computing

Intelligent Technologies and Techniques for Pervasive Computing PDF Author: Kolomvatsos, Kostas
Publisher: IGI Global
ISBN: 1466640391
Category : Computers
Languages : en
Pages : 351

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Book Description
Pervasive computing enables users to interact with information resources in their everyday lives. The development of computational technologies that can exist in ever smaller devices while simultaneously increasing processing power allows such devices to blend seamlessly into tangible environments. Intelligent Technologies and Techniques for Pervasive Computing provides an extensive discussion of such technologies, theories and practices in an attempt to shed light on current trends and issues in the adaption of pervasive systems. Within its pages, students and practitioners of computer science will find both recent developments and practical applications—an overview of the field and how intelligent techniques can help to improve user experience in the distribution and consumption of pertinent, timely information. This book is part of the Advances in Computational Intelligence and Robotics series collection.

Machine Learning Control – Taming Nonlinear Dynamics and Turbulence

Machine Learning Control – Taming Nonlinear Dynamics and Turbulence PDF Author: Thomas Duriez
Publisher: Springer
ISBN: 3319406248
Category : Technology & Engineering
Languages : en
Pages : 229

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Book Description
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.