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From Motor Learning to Interaction Learning in Robots
From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.
Advances in Information and Intelligent Systems
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 Depart...
Constructive Neural Networks
This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks (ICANN 2008) in September 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to the standard method of finding a correct neural architecture by trial-and-error. These algorithms provide an incremental way of building neural networks with reduced topologies for classification problems. Furthermore, these techniques produce not only the multilayer topol...
Intelligent Systems for Knowledge Management
New approaches are needed that could move us towards developing effective systems for problem solving and decision making, systems that can deal with complex and ill-structured situations, systems that can function in information rich environments, systems that can cope with imprecise information, systems that can rely on their knowledge and learn from experience - i.e. intelligent systems. One of the main efforts in intelligent systems development is focused on knowledge and information management which is regarded as the crucial issue in smart decision making support. The 13 Chapters of this book represent a sample of such effort. The overall aim of this book is to provide guidelines to de...
Software Engineering Research, Management and Applications 2009
The 7th ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2009) was held on Hainan Island, China from December 2 – 4. SERA ’09 featured excellent theoretical and practical contributions in the areas of formal methods and tools, requirements engineering, software process models, communication systems and networks, software quality and evaluation, software engineering, networks and mobile computing, parallel/distributed computing, software testing, reuse and metrics, database retrieval, computer security, software architectures and modeling. Our conference officers selected the best 17 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members or the program committee, and underwent further rigorous rounds of review.
Advances in Machine Learning I
Professor Richard S. Michalski passed away on September 20, 2007. Once we learned about his untimely death we immediately realized that we would no longer have with us a truly exceptional scholar and researcher who for several decades had been inf- encing the work of numerous scientists all over the world - not only in his area of expertise, notably machine learning, but also in the broadly understood areas of data analysis, data mining, knowledge discovery and many others. In fact, his influence was even much broader due to his creative vision, integrity, scientific excellence and exceptionally wide intellectual horizons which extended to history, political science and arts. Professor Micha...
Business and Non-profit Organizations Facing Increased Competition and Growing Customers' Demands
We are pleased to introduce our 17th and latest volume from our regular conference: Business and Non-profit Organizations Facing Increased Competitions and Growing Customers’ Demands, which contains articles highlighting the problems of contemporary for-profit and non-profit organizations. The added value is the inclusion of multifaceted aspects of an organization’s functioning, including the sectoral and industrial view. The diversity of the approach to the problems of organization, management, business and economy becomes a valuable interdisciplinary view of the economic reality that surrounds us. The monograph is divided into four sections. In the first section: Business and non-profi...
Multi-Objective Swarm Intelligent Systems
This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.
Parallel Processing and Applied Mathematics
This volume comprises the proceedings of the 6th International Conference on Parallel Processing and Applied Mathematics - PPAM 2005, which was held in Poznan, the industrial, academic and cultural center in the western part of Poland, during September 11–14, 2005.
Mixed Integer Nonlinear Programming
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.
