Complex systems in knowledge-based environments : theory, models and applications
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Bibliographic Information
Complex systems in knowledge-based environments : theory, models and applications
（Studies in computational intelligence, 168）
Springer, c2009
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Includes bibliographical references and author index
Description and Table of Contents
Description
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.
Table of Contents
An Introduction to Complex Systems in the Knowledge-Based Environment.- Uncertainty Representation and Reasoning in Complex Systems.- A Layered Approach to Composition and Interoperation in Complex Systems.- Ontology Driven Data Integration in Heterogeneous Networks.- Complexity and Emergence in Engineering Systems.- Feature Modeling: Managing Variability in Complex Systems.- Semantic Robotics: Cooperative Labyrinth Discovery Robots for Intelligent Environments.- Principles for Effectively Representing Heterogeneous Populations in Multi-agent Simulations.- Ontology Meets Business - Applying Ontology to the Development of Business Information Systems.
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