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Adaptation in Dynamical Systems

Adaptation in Dynamical Systems
Author: Ivan Tyukin
Publisher: Cambridge University Press
Total Pages: 429
Release: 2011-02-17
Genre: Science
ISBN: 1139494163

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In the context of this book, adaptation is taken to mean a feature of a system aimed at achieving the best possible performance, when mathematical models of the environment and the system itself are not fully available. This has applications ranging from theories of visual perception and the processing of information, to the more technical problems of friction compensation and adaptive classification of signals in fixed-weight recurrent neural networks. Largely devoted to the problems of adaptive regulation, tracking and identification, this book presents a unifying system-theoretic view on the problem of adaptation in dynamical systems. Special attention is given to systems with nonlinearly parameterized models of uncertainty. Concepts, methods and algorithms given in the text can be successfully employed in wider areas of science and technology. The detailed examples and background information make this book suitable for a wide range of researchers and graduates in cybernetics, mathematical modelling and neuroscience.


Complex Systems

Complex Systems
Author: Russel J. Stonier
Publisher: IOS Press
Total Pages: 412
Release: 1994
Genre: Computers
ISBN: 9789051991864

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The last few years have seen an extraordinary growth in many areas of complex systems. In the field of synergetics and cooperative behaviour in neural systems a new vocabulary emerged to describe discoveries of wide-ranging and fundamental phenomena, like for example artificial life, biocomplexity, cellular automata, chaos, criticality, fractals, learning systems, neural networks, non-linear dynamics, parallel computation, percolation, self-organization.One of the contributing factors to this growth is the extraordinary increase in computing power. Previously intractable non-linear systems are now amenable to analysis and simulation and parallel computers are ever more important in these areas.The book contains papers exploring many aspects of complex systems, covering theory and applications and deal with material drawn from many different disciplines and specialities.


On Typicality and Adaptation in Driven Dynamical Systems

On Typicality and Adaptation in Driven Dynamical Systems
Author: Pavel Chvykov
Publisher:
Total Pages: 130
Release: 2019
Genre:
ISBN:

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In this work, I consider the possibility of using typicality-type arguments for understanding intractably complex damped-driven dynamical systems. By approximating such dynamics with appropriately constrained random process, I illustrate quantitative predictive power for some aspects of the motion. In particular, I argue that local dynamical stability, or exit rate, of a state is typically sufficient to predict steady-state probability in such systems -- circumventing the classic no-go theorems via our disorder approximation. I then focus on one consequence of this result: that the most likely long-time configurations should also be the dynamically stable ones. In a strongly-driven system, however, such stability may be hard to achieve, and therefore has interesting implications about the corresponding configurations: they must be well-adapted to the details of the driving forces, their dynamical robustness may be viewed in the context of self-healing, and depending on the drive, they can require substantial collective fine-tuning among the system's degrees of freedom. I confirm the emergence of such adapted states in several example systems, both in simulation and in experiment, and verify a quantitative agreement with the predicted scaling between their steady-state probability and local stability. I then explore several arguments and test-cases suggesting further generality of this framework. While it is not yet clear what the precise limits of applicability are for this approach, our results suggest that the intuition it builds can help with prediction and design in a broad class of complex dynamics.


Learning for Adaptive and Reactive Robot Control

Learning for Adaptive and Reactive Robot Control
Author: Aude Billard
Publisher: MIT Press
Total Pages: 425
Release: 2022-02-08
Genre: Technology & Engineering
ISBN: 0262367017

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Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.


Neuronal Dynamics

Neuronal Dynamics
Author: Wulfram Gerstner
Publisher: Cambridge University Press
Total Pages: 591
Release: 2014-07-24
Genre: Computers
ISBN: 1107060834

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This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.


Complex and Adaptive Dynamical Systems

Complex and Adaptive Dynamical Systems
Author: Claudius Gros
Publisher: Springer Science & Business Media
Total Pages: 335
Release: 2010-09-24
Genre: Science
ISBN: 3642047068

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Discover a wide range of findings in quantitative complex system science that help us make sense of our complex world. Written at an introductory level, the book provides an accessible entry into this fascinating and vitally important subject.


Mental Models and Their Dynamics, Adaptation, and Control

Mental Models and Their Dynamics, Adaptation, and Control
Author: Jan Treur
Publisher: Springer Nature
Total Pages: 611
Release: 2022-01-26
Genre: Technology & Engineering
ISBN: 3030858219

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This book introduces a generic approach to model the use and adaptation of mental models, including the control over this. In their mental processes, humans often make use of internal mental models as a kind of blueprints for processes that can take place in the world or in other persons. By internal mental simulation of such a mental model in their brain, they can predict and be prepared for what can happen in the future. Usually, mental models are adaptive: they can be learned, refined, revised, or forgotten, for example. Although there is a huge literature on mental models in various disciplines, a systematic account of how to model them computationally in a transparent manner is lacking. This approach allows for computational modeling of humans using mental models without a need for any algorithmic or programming skills, allowing for focus on the process of conceptualizing, modeling, and simulating complex, real-world mental processes and behaviors. The book is suitable for and is used as course material for multidisciplinary Master and Ph.D. students.


An Introduction to Self-adaptive Systems

An Introduction to Self-adaptive Systems
Author: Danny Weyns
Publisher: John Wiley & Sons
Total Pages: 288
Release: 2020-10-05
Genre: Technology & Engineering
ISBN: 1119574943

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A concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.


Small Groups as Complex Systems

Small Groups as Complex Systems
Author: Holly Arrow
Publisher: SAGE Publications
Total Pages: 345
Release: 2000-03-21
Genre: Business & Economics
ISBN: 1452238502

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"The emphasis on change at many levels of organization is critically important as is the first attempt to integrate sophisticated theory and research in organization psychology (e.g., Gersick, Hackman) with social psychological models of development such as Moreland and Levine." --Reuben M. Baron, Emeritus, University of Connecticut "Arrow, McGrath, and Berdahl′s ′Small Groups as Complex Systems′ will change the way you think about groups, the way you think about research, and even the way you think about science." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "The book is excellent, one of those very rare works that will have substantial impact on the field. I would use the book without hesitation in any advanced graduate seminar dealing with groups." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "A conceptually elegant analysis of groups as systems. Although the systems approach has been growing more influential in various fields of social psychology in the last ten years, no one has put forward a definitive analysis that applies with fidelity the general systems approach to group processes. McGrath and his colleagues fill that gap, not by paying lip service to popular scientific concepts such as recursive causality, open systems, attractors, and complexity theory, but by fully integrating these concepts into their no-nonsense analysis of such group level processes as formation, task performance, composition, development, and termination. Empirical work is folded into the theoretical mix along the way, but the focus is unrelentingly conceptual with the result that the authors deliver on their promise of developing a powerful, unified theory of group dynamics." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "Theirs is an ambitious book. They have profound ramifications for experimental social psychology. It is worth mentioning that AMD (Arrow, McGrarth, and Berdahl) list an ethnographic approach, which often implies the adoption of hermeneutic and semiotic methods (a hallmark of the anti-Enlightenment tradition in psychology), as a possible way forward." --Yoshihisa Kashima, American Journal of Psychology What are groups? How do they behave? Arrow, McGrath, and Berdahl answer these questions by developing a general theory of small groups as complex systems. Basing their theory on concepts distilled from general systems theory, dynamical systems theory, and complexity and chaos theory, they explore groups as adaptive, dynamic systems that are driven by interactions among group members as well as between the group and its embedding contexts. In addition, they consider not only the group′s members and their distribution of attributes, but also the group′s tasks and technology in order to understand how those members, tasks, and tools are intertwined, coordinated, and adjusted. Throughout the book, the authors focus our attention on relationships among people, tools, and tasks that are activated by a combination of individual and collective purposes and goals that change and evolve as the group interacts over time.