With the developments and intersection of science and engineering, cognitive informatics has emerged as a new and intriguing field of study which investigates the natural intelligence and internal information processing mechanisms of the brain as well as the methods involved in perception and cognition. Cognitive Informatics for Revealing Human Cognition: Knowledge Manipulations in Natural Intelligence presents a comprehensive collection of research that builds a link between natural and life sciences with informatics and computer science. This book is practical for researchers, practitioners, and graduate students interested in investigating cognitive mechanisms and the human information processes.

As both intelligence and software science revolutionizes the modern world, the contributions that each make to the other combine into a new transdisciplinary field. Breakthroughs in Software Science and Computational Intelligence charts the new ground broken by researchers exploring these two disciplines. A vital resource to students and practitioners working in computer science, theoretical software engineering, cognitive science, cognitive informatics, and intelligence science, this book establishes itself in this new field, emphasizing the abundance of future applications and advancement.

The junction of software development and engineering combined with the study of intelligence has created a bustling intersection of theory, design, engineering, and conceptual thought. Software and Intelligent Sciences: New Transdisciplinary Findings sits at a crossroads and informs advanced researchers, students, and practitioners on the developments in computer science, theoretical software engineering, cognitive science, cognitive informatics, and intelligence science. The crystallization of accumulated knowledge by the fertilization of these areas, have led to the emergence of a transdisciplinary field known as software and intelligence sciences, to which this book is an important contribution and a resource for both fields alike.

Creating a link between a number of natural science and life science disciplines, the emerging field of cognitive informatics presents a transdisciplinary approach to the internal information processing mechanisms and processes of the brain and natural intelligence.""Novel Approaches in Cognitive Informatics and Natural Intelligence"" penetrates the academic field to offer the latest advancements in cognitive informatics and natural intelligence. This book covers the five areas of cognitive informatics, natural intelligence, autonomic computing, knowledge science, and relevant development, to provide researchers, academicians, students, and practitioners with a ready reference to the latest findings.

Continuous developments in software and intelligence sciences have brought together the studies of both natural and machine intelligence and the relationship between the function of the brain and the abstract soft mind; creating a new multidisciplinary field of study. Advances in Abstract Intelligence and Soft Computing brings together the latest research in computer science: theoretical software engineering, cognitive science and informatics, and also their influence on the processes of natural and machine intelligence. This book is a collection of widespread research in the constant expansions on this emerging discipline.

Cognitive informatics is a multidisciplinary field that acts as the bridge between natural science and information science. Specifically, it investigates the potential applications of information processing and natural intelligence to science and engineering disciplines. Transdisciplinary Advancements in Cognitive Mechanisms and Human Information Processing examines innovative research in the emerging, multidisciplinary field of cognitive informatics. Researchers, practitioners and students can benefit from discussions of the connections between natural science and informatics that are investigated in this fundamental collection of cognitive informatics research. This book provides information on the interrelation of the multidisciplinary research area of Cognitive Informatics and the transdisciplinary study of Natural Intelligence.

Thought, comprehension, and intelligence are everyday concepts that are so pervasive through the lives of every human being that people scarcely think about them at all. These processes are so complex under the surface, however, that a fully developed scientific discipline is necessary to explore these topics. Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications covers the intricate worlds of thought, comprehension, intelligence, and knowledge through the scientific field of Cognitive Science. This groundbreaking reference contains research from global experts, covering topics that have been pivotal at major conferences covering Cognitive Science topics.

Cognitive Informatics (CI) is the science of cognitive information processing and its applications in cognitive computing. CI is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain. Advances and engineering applications of CI have led to the emergence of cognitive computing and the development of Cognitive Computers (CCs) that reason and learn. As initiated by Yingxu Wang and his colleagues, CC has emerged and developed based on the transdisciplinary research in CI, abstract intelligence (aI), and denotational mathematics after the inauguration of the series of IEEE International Conference on Cognitive Informatics since 2002 at Univ. of Calgary, Stanford Univ., and Tsinghua Univ., etc. This volume in LNCS (subseries of Computational Intelligence), LNCI 323, edited by Y. Wang, D. Zhang, and W. Kinsner, presents the latest development in cognitive informatics and cognitive computing. The book focuses on the explanation of cognitive models of the brain, the layered reference model of the brain, the fundamental mechanisms of abstract intelligence, and the implementation of computational intelligence by autonomous inference and learning engines based on CCs.

Software engineering is playing an increasingly significant role in computing and informatics, necessitated by the complexities inherent in large-scale software development. To deal with these difficulties, the conventional life-cycle approaches to software engineering are now giving way to the "process system" approach, encompassing development methods, infrastructure, organization, and management. Until now, however, no book fully addressed process-based software engineering or set forth a fundamental theory and framework of software engineering processes.
Software Engineering Processes: Principles and Applications does just that. Within a unified framework, this book presents a comparative analysis of current process models and formally describes their algorithms. It systematically enables comparison between current models, avoidance of ambiguity in application, and simplification of manipulation for practitioners.
The authors address a broad range of topics within process-based software engineering and the fundamental theories and philosophies behind them. They develop a software engineering process reference model (SEPRM) to show how to solve the problems of different process domains, orientations, structures, taxonomies, and methods. They derive a set of process benchmarks-based on a series of international surveys-that support validation of the SEPRM model. Based on their SEPRM model and the unified process theory, they demonstrate that current process models can be integrated and their assessment results can be transformed between each other.
Software development is no longer just a black art or laboratory activity. It is an industrialized process that requires the skills not just of programmers, but of organization and project managers and quality assurance specialists. Software Engineering Processes: Principles and Applications is the key to understanding, using, and improving upon effective engineering procedures for software development.

Cognitive Informatics (CI) is the science of cognitive information processing and its applications in cognitive computing. CI is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain. Advances and engineering applications of CI have led to the emergence of cognitive computing and the development of Cognitive Computers (CCs) that reason and learn. As initiated by Yingxu Wang and his colleagues, CC has emerged and developed based on the transdisciplinary research in CI, abstract intelligence (aI), and denotational mathematics after the inauguration of the series of IEEE International Conference on Cognitive Informatics since 2002 at Univ. of Calgary, Stanford Univ., and Tsinghua Univ., etc. This volume in LNCS (subseries of Computational Intelligence), LNCI 323, edited by Y. Wang, D. Zhang, and W. Kinsner, presents the latest development in cognitive informatics and cognitive computing. The book focuses on the explanation of cognitive models of the brain, the layered reference model of the brain, the fundamental mechanisms of abstract intelligence, and the implementation of computational intelligence by autonomous inference and learning engines based on CCs.

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods.

The fifth volume of the Transactions on Computational Science journal, edited by Yingxu Wang and Keith C.C. Chan, is devoted to the subject of cognitive knowledge representation. This field of study focuses on the internal knowledge representation mechanisms of the brain and how these can be applied to computer science and engineering. The issue includes the latest research results in internal knowledge representation at the logical, functional, physiological, and biological levels and describes their impacts on computing, artificial intelligence, and computational intelligence.

The denotational and expressive needs in cognitive informatics, computational intelligence, software engineering, and knowledge engineering have led to the development of new forms of mathematics collectively known as denotational mathematics. Denotational mathematics is a category of mathematical structures that formalize rigorous expressions and long-chain inferences of system compositions and behaviors with abstract concepts, complex relations, and dynamic processes. Typical paradigms of denotational mathematics are concept algebra, system algebra, Real-Time Process Algebra (RTPA), Visual Semantic Algebra (VSA), fuzzy logic, and rough sets. A wide range of applications of denotational mathematics have been identified in many modern science and engineering disciplines that deal with complex and intricate mathematical entities and structures beyond numbers, Boolean variables, and traditional sets. This issue of Springer's Transactions on Computational Science on Denotational Mathematics for Computational Intelligence presents a snapshot of current research on denotational mathematics and its engineering applications. The volume includes selected and extended papers from two international conferences, namely IEEE ICCI 2006 (on Cognitive Informatics) and RSKT 2006 (on Rough Sets and Knowledge Technology), as well as new contributions. The following four important areas in denotational mathem- ics and its applications are covered: Foundations and applications of denotational mathematics, focusing on: a) c- temporary denotational mathematics for computational intelligence; b) deno- tional mathematical laws of software; c) a comparative study of STOPA and RTPA; and d) a denotational mathematical model of abstract games.