Bücher der Reihe Studies in Computational Intelligence

This book is a collection of chapters on the state of art in the area of intelligent machines. and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.

This book explores all the latest research in the area of advanced intelligent paradigms in computer games. It presents a sample of the most recent research concerning the application of computational intelligence techniques and internet technology in computer games. computational intelligence in racing games;

As opposed to the Monte Carlo strategies, in which the population is sampled according to the uniform probability distribution over the search domain, genetic algorithms modify the probability distribution at each step.

Support vector machines (SVMs) are one of the most active research areas in machine learning. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer an explanation capability.

This book presents hardware-efficient algorithms and FPGA implementations for two robotic tasks, namely exploration and landmark determination. The work identifies scenarios for mobile robotics where parallel processing and selective shutdown offered by FPGAs are invaluable.

In a highly authoritative and systematic manner, this book offers an in-depth treatment of the essence of the case-based reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm.

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.

Bioinformatics involve the creation and advancement of algorithms using techniques including computational intelligence, applied mathematics and statistics, informatics, and biochemistry to solve biological problems usually on the molecular level.

Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering.

The primary aim of this up-to-date research book is to report a sample of the most recent advances in the field of intelligent interactive systems in knowledge-based environments.

The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches.

Optimization problems are of great importance across a broad range of fields. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

This book contains papers presented at the International Symposium on Elect- magnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF'07 which was held in Prague, the Czech Republic, from September 13 to 15, 2007.

This book collects selected papers by authors for CODATA 2006, which are relevant to the acquisition of knowledge and the assessment of risk and opportunity that comes from combining data from a number of different disciplines.

Just over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear.

Statistical implicative analysis is a data analysis method created by Regis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining.

The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

This book is a composition of different points of view regarding the application of Computational Intelligence techniques and methods to Remote Sensing data and applications. The classes of images dealt with are mostly multispectral-hyperspectral images.

This book includes 37 chapters which discuss examples of the application of intelligence technologies to five separate fields that reflect the main streams of practical and scientific interest within the computer related community.

Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable.

This book represents the peer-reviewed proceedings of the Second International Symposium on Intelligent Distributed Computing - IDC 2008 held in Catania, Italy during September 18-19, 2008.

One of the most challenging issues for the intelligent decision systems is to effectively manage the large-scale complex distributed environments such as computational clouds, grids, ad hoc and P2P networks, under the different types of users, their relations, and real-world uncertainties.

This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.

"Intelligent Data Mining - Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications.

This book presents a collection of works discussing terrorism informatics, information sharing, data mining, intelligence and crime analysis, infrastructure protection, privacy protection, information surveillance, and emergency response.

Important features include the detailed overview of the various novel metaheuristic scheduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field.

Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed.The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.

This book is edited from some aspects of e-commerce researches including theoretical mechanism design of trading based on auctions, allocation mechanism based on negotiation among multi-agent, case-study and analysis of e-trading, data engineering issues in e-commerce, and so on.

Power system reliability is the focus of intensive study due to its critical role in providing energy supply to modern society.

The text here provides the reader with an in-depth overview and analysis of the fundamental methods and techniques developed following G. Voronoi's ground-breaking ideas, in the context of the vast and increasingly growing area of computational intelligence.