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This is not a purely mathematical book. It presents the basic principle of wavelet theory to electrical and electronic engineers, computer scientists, and students, as well as the ideas of how wavelets can be applied to pattern recognition. It also contains many novel research results from the authors' research team.

An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals. Responding to different stimuli received from its task environment, the agent may select and exhibit different behavioral patterns. The behavioral patterns may be carefully predefined or dynamically acquired by the agent based on some learning and adaptation mechanism(s). In order to achieve structural flexibility, reliability through redundancy, adaptability, and reconfigurability in...

Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution.
After reading...

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc.

Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system...

This book is a collection of high quality technical papers contributed by active researchers and leading practitioners in intelligent agent technology. It offers a closer look at the state-of-the-art in the development of intelligent agents, and examines in depth the underlying logical, cognitive, physical, and biological foundations as well as the performance characteristics of various approaches in intelligent agent technology. It will stimulate the development of new models, new methodologies, and new tools for building a variety of embodiments of agent-based systems.

The past few years have witnessed rapid scienti?c and technological devel- ments in human-centered, seamless computing environments, interfaces, de- ces, and systems with applications ranging from business and communication to entertainment and learning. These developments are collectively best charac- rized as Active Media Technology (AMT), a new area of information technology and computer science that emphasizes the proactive, seamless roles of interfaces and systems as well as new digital media in all aspects of human life. This - lume contains the papers presented at the Sixth...

This book constitutes the refereed proceedings of the 5th International Conference on Active Media Technology, AMT 2009, held in Beijing, China, in October 2009. The 47 revised full papers and the 6 keynote talks were carefully reviewed and selected. The papers reflect the shared forum for researchers and practitioniers from diverse fields, such as computer science, information technology, artificial intelligence, media engineering, economics, data mining, data and knowledge engineering, intelligent agent technology, human computer interaction, complex systems and systems science. The book...

Spatial reasoning and planning is a core constituent in robotics, graphics, computer-aided design, and geographic information systems.

After a review of previous work in the related areas, Liu and Daneshmend present here a unified framework for qualitative spatial representation and reasoning, which enables the generation of solutions to spatial problems where the geometric knowledge is imprecise. The approach utilizes qualitative spatial representation and reasoning integrated with a quantitative search procedure based on simulated annealing. Many graphical illustrations...

Spatial reasoning and planning is a core constituent in robotics, graphics, computer-aided design, and geographic information systems.

After a review of previous work in the related areas, Liu and Daneshmend present here a unified framework for qualitative spatial representation and reasoning, which enables the generation of solutions to spatial problems where the geometric knowledge is imprecise. The approach utilizes qualitative spatial representation and reasoning integrated with a quantitative search procedure based on simulated annealing. Many graphical illustrations...

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc.

Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system...

Intelligent Data Engineering and Automated Learning (IDEAL) was initially a biennial forum dedicated to emerging and challenging topics in intelligent data analysis, knowledge discovery, and statistical and computational learning. The huge success of recent IDEAL conferences and the continuous growth of the ?eld have compelled it to become an annual conference after 2003. It is now a major international, interdisciplinary event covering subjects from data mining, inf- mation retrieval and management, autonomous learning, and agents to ?nancial engineering, neural networks, emerging learning...

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models.

The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book...

Over the past decade there has been an explosion of developments in mixed e?ects models and their applications. This book concentrates on two major classes of mixed e?ects models, linear mixed models and generalized linear mixed models, with the intention of o?ering an up-to-date account of theory and methods in the analysis of these models as well as their applications in various ?elds. The ?rst two chapters are devoted to linear mixed models. We classify l- ear mixed models as Gaussian (linear) mixed models and non-Gaussian linear mixed models. There have been extensive studies in...

In a way, the world is made up of approximations, and surely there is no exception in the world of statistics. In fact, approximations, especially large sample approximations, are very important parts of both theoretical and - plied statistics.TheGaussiandistribution, alsoknownasthe normaldistri- tion, is merelyonesuchexample, dueto thewell-knowncentrallimittheorem. Large-sample techniques provide solutions to many practical problems; they simplify our solutions to di?cult, sometimes intractable problems; they j- tify our solutions; and they guide us to directions of improvements. On the...

Mixed-effects models have found broad applications in various fields. As a result, the interest in learning and using these models is rapidly growing.

Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function.

The authors deal with linear optimization, nonlinear...