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This volume examines the application of swarm intelligence in data mining, addressing the issues of swarm intelligence and data mining using novel intelligent approaches. The book comprises 11 chapters including an introduction reviewing fundamental definitions and important research challenges. Important features include a detailed overview of swarm intelligence and data mining paradigms, focused coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and contributions by pioneers in the field.
This edited volume deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business and commerce. It comprises 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
This book presents the results of research into one of the most complex and difficult areas - research into thinking and understanding. The research was carried out at the newly founded Queen Jadwiga Research Institute of Understanding and is focused on the problem of visual understanding and visual thinking. The authors believe this is the first book to attempt to investigate the complexity of visual thinking problems in the context of building the thinking machine.
Trends in Neural Computation includes twenty chapters contributed by leading experts or formed by extending well-selected papers presented in the 2005 International Conference on Natural Computation. The book reviews the latest progress in a range of different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks – architectures and learning algorithms and their applications in real-world problems.
This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.
Realizing the growing importance of semantic adaptation and personalization of media, the editors of this book brought together leading researchers and practitioners of the field to discuss the state-of-the-art, and explore emerging exciting developments. This volume comprises extended versions of selected papers presented at the 1st International Workshop on Semantic Media Adaptation and Personalization (SMAP 2006), which took place in Athens in December 2006.
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.
Researchers have obtained robots that display an amazing slew of behaviors and perform a multitude of tasks, including perception of environment, negotiating rough terrain, and pushing boxes. This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.
Business organizations and governments are nowadays developing and providing internet based electronic services (e-services) featuring various intelligent functions. This book offers a thorough introduction and systematic overview of the new field e-service intelligence. It covers the state-of-the-art of e-service intelligence including both theorems and applications, and a broad range of topics are discussed.
Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.