Unified Computational Intelligence for Complex Systems

Unified Computational Intelligence for Complex Systems

Author: John Seiffertt

Publisher: Springer Science & Business Media

Published: 2010-07-15

Total Pages: 123

ISBN-13: 3642031803

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Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.


Book Synopsis Unified Computational Intelligence for Complex Systems by : John Seiffertt

Download or read book Unified Computational Intelligence for Complex Systems written by John Seiffertt and published by Springer Science & Business Media. This book was released on 2010-07-15 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.

Unified Computational Intelligence for Complex Systems

Unified Computational Intelligence for Complex Systems

Author: John Seiffertt

Publisher: Springer

Published: 2010-07-01

Total Pages: 150

ISBN-13: 9783642031793

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Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.


Book Synopsis Unified Computational Intelligence for Complex Systems by : John Seiffertt

Download or read book Unified Computational Intelligence for Complex Systems written by John Seiffertt and published by Springer. This book was released on 2010-07-01 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.

Complex Systems in Knowledge-based Environments: Theory, Models and Applications

Complex Systems in Knowledge-based Environments: Theory, Models and Applications

Author: Andreas Tolk

Publisher: Springer

Published: 2008-12-11

Total Pages: 272

ISBN-13: 3540880755

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The tremendous growth in the availability of inexpensive computing power and easy availability of computers have generated tremendous interest in the design and imp- mentation of Complex Systems. Computer-based solutions offer great support in the design of Complex Systems. Furthermore, Complex Systems are becoming incre- ingly complex themselves. This research book comprises a selection of state-of-the-art contributions to topics dealing with Complex Systems in a Knowledge-based En- ronment. Complex systems are ubiquitous. Examples comprise, but are not limited to System of Systems, Service-oriented Approaches, Agent-based Systems, and Complex Distributed Virtual Systems. These are application domains that require knowledge of engineering and management methods and are beyond the scope of traditional systems. The chapters in this book deal with a selection of topics which range from unc- tainty representation, management and the use of ontological means which support and are large-scale business integration. All contributions were invited and are based on the recognition of the expertise of the contributing authors in the field. By colle- ing these sources together in one volume, the intention was to present a variety of tools to the reader to assist in both study and work. The second intention was to show how the different facets presented in the chapters are complementary and contribute towards this emerging discipline designed to aid in the analysis of complex systems.


Book Synopsis Complex Systems in Knowledge-based Environments: Theory, Models and Applications by : Andreas Tolk

Download or read book Complex Systems in Knowledge-based Environments: Theory, Models and Applications written by Andreas Tolk and published by Springer. This book was released on 2008-12-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tremendous growth in the availability of inexpensive computing power and easy availability of computers have generated tremendous interest in the design and imp- mentation of Complex Systems. Computer-based solutions offer great support in the design of Complex Systems. Furthermore, Complex Systems are becoming incre- ingly complex themselves. This research book comprises a selection of state-of-the-art contributions to topics dealing with Complex Systems in a Knowledge-based En- ronment. Complex systems are ubiquitous. Examples comprise, but are not limited to System of Systems, Service-oriented Approaches, Agent-based Systems, and Complex Distributed Virtual Systems. These are application domains that require knowledge of engineering and management methods and are beyond the scope of traditional systems. The chapters in this book deal with a selection of topics which range from unc- tainty representation, management and the use of ontological means which support and are large-scale business integration. All contributions were invited and are based on the recognition of the expertise of the contributing authors in the field. By colle- ing these sources together in one volume, the intention was to present a variety of tools to the reader to assist in both study and work. The second intention was to show how the different facets presented in the chapters are complementary and contribute towards this emerging discipline designed to aid in the analysis of complex systems.

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems

Author: Yeliz Karaca

Publisher: Academic Press

Published: 2022-06-22

Total Pages: 352

ISBN-13: 0323886167

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Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems. Constructs and presents a multifarious approach for critical decision-making processes embodying paradoxes and uncertainty. Includes a combination of theory and applications with regard to multi-chaos, fractal and multi-fractional as well as AI of different complex systems and many-body systems. Provides readers with a bridge between application of advanced computational mathematical methods and AI based on comprehensive analyses and broad theories.


Book Synopsis Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems by : Yeliz Karaca

Download or read book Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems written by Yeliz Karaca and published by Academic Press. This book was released on 2022-06-22 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems. Constructs and presents a multifarious approach for critical decision-making processes embodying paradoxes and uncertainty. Includes a combination of theory and applications with regard to multi-chaos, fractal and multi-fractional as well as AI of different complex systems and many-body systems. Provides readers with a bridge between application of advanced computational mathematical methods and AI based on comprehensive analyses and broad theories.

Computational Intelligence in Intelligent Data Analysis

Computational Intelligence in Intelligent Data Analysis

Author: Christian Moewes

Publisher: Springer

Published: 2012-08-23

Total Pages: 298

ISBN-13: 3642323782

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Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.


Book Synopsis Computational Intelligence in Intelligent Data Analysis by : Christian Moewes

Download or read book Computational Intelligence in Intelligent Data Analysis written by Christian Moewes and published by Springer. This book was released on 2012-08-23 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.

Computational Intelligence for Modelling Complex Systems

Computational Intelligence for Modelling Complex Systems

Author: Tshilidzi Marwala

Publisher:

Published: 2007

Total Pages: 147

ISBN-13: 9788190436212

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Book Synopsis Computational Intelligence for Modelling Complex Systems by : Tshilidzi Marwala

Download or read book Computational Intelligence for Modelling Complex Systems written by Tshilidzi Marwala and published by . This book was released on 2007 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Advances in Information and Intelligent Systems

Advances in Information and Intelligent Systems

Author: Zbigniew W. Ras

Publisher: Springer

Published: 2009-10-15

Total Pages: 353

ISBN-13: 3642041418

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The College of Computing and Informatics (CCI) at UNC-Charlotte has three departments: Computer Science, Software and Information Systems, and Bioinformatics and Genomics. The Department of Computer Science offers study in a variety of specialized computing areas such as database design, knowledge systems, computer graphics, artificial intelligence, computer networks, game design, visualization, computer vision, and virtual reality. The Department of Software and Information Systems is primarily focused on the study of technologies and methodologies for information system architecture, design, implementation, integration, and management with particular emphasis on system security. The Department of Bioinformatics and Genomics focuses on the discovery, development and application of novel computational technologies to help solve important biological problems. This volume gives an overview of research done by CCI faculty in the area of Information & Intelligent Systems. Presented papers focus on recent advances in four major directions: Complex Systems, Knowledge Management, Knowledge Discovery, and Visualization. A major reason for producing this book was to demonstrate a new, important thrust in academic research where college-wide interdisciplinary efforts are brought to bear on large, general, and important problems. As shown in the research described here, these efforts need not be formally organized joint undertakings (through parts could be) but are rather a convergence of interests around grand themes.


Book Synopsis Advances in Information and Intelligent Systems by : Zbigniew W. Ras

Download or read book Advances in Information and Intelligent Systems written by Zbigniew W. Ras and published by Springer. This book was released on 2009-10-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: The College of Computing and Informatics (CCI) at UNC-Charlotte has three departments: Computer Science, Software and Information Systems, and Bioinformatics and Genomics. The Department of Computer Science offers study in a variety of specialized computing areas such as database design, knowledge systems, computer graphics, artificial intelligence, computer networks, game design, visualization, computer vision, and virtual reality. The Department of Software and Information Systems is primarily focused on the study of technologies and methodologies for information system architecture, design, implementation, integration, and management with particular emphasis on system security. The Department of Bioinformatics and Genomics focuses on the discovery, development and application of novel computational technologies to help solve important biological problems. This volume gives an overview of research done by CCI faculty in the area of Information & Intelligent Systems. Presented papers focus on recent advances in four major directions: Complex Systems, Knowledge Management, Knowledge Discovery, and Visualization. A major reason for producing this book was to demonstrate a new, important thrust in academic research where college-wide interdisciplinary efforts are brought to bear on large, general, and important problems. As shown in the research described here, these efforts need not be formally organized joint undertakings (through parts could be) but are rather a convergence of interests around grand themes.

Collectives and the Design of Complex Systems

Collectives and the Design of Complex Systems

Author: Kagan Tumer

Publisher: Springer Science & Business Media

Published: 2004

Total Pages: 340

ISBN-13: 9780387401652

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With the advent of extremely affordable computing power, the world is becoming filled with distributed systems of computationally sophisticated components. However, no current scientific discipline offers a thorough understanding of the relation of such "collectives" and how well they meet performance criteria. "Collectives and Design of Complex Systems" lays the foundation for the study of collective intelligence and how these entities can be developed to yield optimal performance. Using an approach that integrates key theoretical principles with applications in real-world scenarios, the author surveys the latest research on the dynamics of collectives, their artificial intelligence aspects, and critical design issues pertaining to them.


Book Synopsis Collectives and the Design of Complex Systems by : Kagan Tumer

Download or read book Collectives and the Design of Complex Systems written by Kagan Tumer and published by Springer Science & Business Media. This book was released on 2004 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of extremely affordable computing power, the world is becoming filled with distributed systems of computationally sophisticated components. However, no current scientific discipline offers a thorough understanding of the relation of such "collectives" and how well they meet performance criteria. "Collectives and Design of Complex Systems" lays the foundation for the study of collective intelligence and how these entities can be developed to yield optimal performance. Using an approach that integrates key theoretical principles with applications in real-world scenarios, the author surveys the latest research on the dynamics of collectives, their artificial intelligence aspects, and critical design issues pertaining to them.

Methods of computational intelligence for modeling and data representation of complex systems

Methods of computational intelligence for modeling and data representation of complex systems

Author: VÁRKONYINÉ KÓCZY ANNAMÁRIA.

Publisher:

Published: 2008

Total Pages: 0

ISBN-13:

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Book Synopsis Methods of computational intelligence for modeling and data representation of complex systems by : VÁRKONYINÉ KÓCZY ANNAMÁRIA.

Download or read book Methods of computational intelligence for modeling and data representation of complex systems written by VÁRKONYINÉ KÓCZY ANNAMÁRIA. and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Intelligence Paradigms

Computational Intelligence Paradigms

Author: Mika Sato-Ilic

Publisher: Springer

Published: 2008-06-17

Total Pages: 281

ISBN-13: 3540794743

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System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex systems which are intelligent and robust. The book includes a sample of research on the innovative applications of advanced computational intelligence paradigms. The characteristics of computational intelligence paradigms such as learning, generalization based on learned knowledge, knowledge extraction from imprecise and incomplete data are the extremely important for the implementation of intelligent machines. The chapters include architectures of computational intelligence paradigms, knowledge discovery, pattern classification, clusters, support vector machines and gene linkage analysis. We believe that the research on computational intelligence will simulate great interest among designers and researchers of complex systems. It is important to use the fusion of various constituents of computational intelligence to offset the demerits of one paradigm by the merits of another.


Book Synopsis Computational Intelligence Paradigms by : Mika Sato-Ilic

Download or read book Computational Intelligence Paradigms written by Mika Sato-Ilic and published by Springer. This book was released on 2008-06-17 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex systems which are intelligent and robust. The book includes a sample of research on the innovative applications of advanced computational intelligence paradigms. The characteristics of computational intelligence paradigms such as learning, generalization based on learned knowledge, knowledge extraction from imprecise and incomplete data are the extremely important for the implementation of intelligent machines. The chapters include architectures of computational intelligence paradigms, knowledge discovery, pattern classification, clusters, support vector machines and gene linkage analysis. We believe that the research on computational intelligence will simulate great interest among designers and researchers of complex systems. It is important to use the fusion of various constituents of computational intelligence to offset the demerits of one paradigm by the merits of another.