Machine Learning In Natural Complex Systems
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Machine Learning In Natural Complex Systems
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Author : Andre Gruning
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-11
Machine Learning In Natural Complex Systems written by Andre Gruning and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Science categories.
Adaptation In Natural And Artificial Systems
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Author : John H. Holland
language : en
Publisher: MIT Press
Release Date : 1992-04-29
Adaptation In Natural And Artificial Systems written by John H. Holland and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-04-29 with Psychology categories.
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics. Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.
Abstraction In Artificial Intelligence And Complex Systems
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Author : Lorenza Saitta
language : en
Publisher: Springer
Release Date : 2013-05-20
Abstraction In Artificial Intelligence And Complex Systems written by Lorenza Saitta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.
Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models.
Machine Learning In Complex Networks
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Author : Thiago Christiano Silva
language : en
Publisher: Springer
Release Date : 2016-01-28
Machine Learning In Complex Networks written by Thiago Christiano Silva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-28 with Computers categories.
This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning. Such matter has practical importance and is not often found in the literature. With the goal of validating these techniques for solving real problems, simulations on broadly accepted databases are conducted. Still in this book, we present a hybrid supervised classification technique that combines both low and high orders of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features, while the latter measures the compliance of the test instances with the pattern formation of the data. We show that the high level technique can realize classification according to the semantic meaning of the data. This book intends to combine two widely studied research areas, machine learning and complex networks, which in turn will generate broad interests to scientific community, mainly to computer science and engineering areas.
Predictive Approaches To Control Of Complex Systems
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Author : Gorazd Karer
language : en
Publisher: Springer
Release Date : 2012-09-20
Predictive Approaches To Control Of Complex Systems written by Gorazd Karer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-20 with Technology & Engineering categories.
A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequently encountered complex dynamical phenomena and are practically applicable in the proposed predictive control approaches. Furthermore, unsupervised learning methods that can be used for complex-system identification are treated. Finally, several useful predictive control algorithms for complex systems are proposed and their particular advantages and drawbacks are discussed. The presented modeling, identification and control approaches are complemented by illustrative examples. The book is aimed towards researches and postgraduate students interested in modeling, identification and control, as well as towards control engineers needing practically usable advanced control methods for complex systems.
Complex Engineered Systems
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Author : Dan Braha
language : en
Publisher: Springer
Release Date : 2007-06-24
Complex Engineered Systems written by Dan Braha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-24 with Science categories.
Recent advances in science and technology have led to a rapid increase in the complexity of most engineered systems. In many notable cases, this change has been a qualitative one rather than merely one of magnitude. A new class of Complex Engineered Systems (CES) has emerged as a result of technologies such as the Internet, GPS, wireless networking, micro-robotics, MEMS, fiber-optics and nanotechnology. These complex engineered systems are composed of many heterogeneous subsystems and are characterized by observable complex behaviors that emerge as a result of nonlinear spatio-temporal interactions among the subsystems at several levels of organization and abstraction. Examples of such systems include the World-Wide Web, air and ground traffic networks, distributed manufacturing environments, and globally distributed supply networks, as well as new paradigms such as self-organizing sensor networks, self-configuring robots, swarms of autonomous aircraft, smart materials and structures, and self-organizing computers. Understanding, designing, building and controlling such complex systems is going to be a central challenge for engineers in the coming decades.
Proceedings Of The 3rd International Conference On Computer Science S Complex Systems And Their Applications
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Author : Toufik Marir
language : en
Publisher: Springer Nature
Release Date : 2025-07-11
Proceedings Of The 3rd International Conference On Computer Science S Complex Systems And Their Applications written by Toufik Marir and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Technology & Engineering categories.
This book features a diverse collection of high-quality papers covering the latest advancements in Artificial Intelligence and its Applications, Cybersecurity, Software Engineering, Emergent Technologies, Networks and Embedded Systems. The ICCSA’2024 Proceedings bring together the latest research presented at the International Conference on Computer Science's Complex Systems and Their Applications (ICCSA’2024), held on November 13–14, 2024, in Oum El Bouaghi, Algeria. Edited by leading experts in the field, this publication showcases innovative methodologies, theoretical breakthroughs, and real-world applications that shape the future of complex systems. With contributions from renowned researchers from around the world, who carefully selected the best research contributions for this international conference, the ICCSA’2024 Proceedings stand as a valuable resource for academics, industry professionals, and students seeking insights into the evolving landscape of complex systems. Whether you are interested in complex systems and their engineering or their interdisciplinary applications, this book provides comprehensive and in-depth coverage of the most pressing challenges and transformative innovations in this field.
Reservoir Computing
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Author : Kohei Nakajima
language : en
Publisher: Springer Nature
Release Date : 2021-08-05
Reservoir Computing written by Kohei Nakajima and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-05 with Computers categories.
This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware implementations. 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. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications. The book is sub-structured into two major parts: theory and physical implementations. Both parts consist of a compilation of chapters, authored by leading experts in their respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamical systems context. With this broadened perspective, RC is not restricted to the area of machine learning but is being connected to a much wider class of systems. The second part of the book focuses on the utilization of physical dynamical systems as reservoirs, a framework referred to as physical reservoir computing. A variety of physical systems and substrates have already been suggested and used for the implementation of reservoir computing. Among these physical systems which cover a wide range of spatial and temporal scales, are mechanical and optical systems, nanomaterials, spintronics, and quantum many body systems. This book offers a valuable resource for researchers (Ph.D. students and experts alike) and practitioners working in the field of machine learning, artificial intelligence, robotics, neuromorphic computing, complex systems, and physics.
Machine Learning Predictive Analytics And Optimization In Complex Systems
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Author : John Joseph, Ferdin Joe
language : en
Publisher: IGI Global
Release Date : 2025-06-27
Machine Learning Predictive Analytics And Optimization In Complex Systems written by John Joseph, Ferdin Joe and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Computers categories.
The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists.
Complex Systems
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Author : Russel J. Stonier
language : en
Publisher: IOS Press
Release Date : 1994
Complex Systems written by Russel J. Stonier and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
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.