Soft computing is a branch of computing which, unlike hard computing, can deal with uncertain, imprecise and inexact data. The three constituents of soft computing are fuzzy-logic-based computing, neurocomputing, and genetic algorithms. Fuzzy logic contributes the capability of approximate reasoning, neurocomputing offers function approximation and learning capabilities, and genetic algorithms provide a methodology for systematic random search and optimization. These three capabilities are combined in a complementary and synergetic fashion.This book presents a cohesive set of contributions dealing with important issues and applications of soft computing in systems and control technology. The contributions include state-of-the-art material, mathematical developments, fresh results, and how-to-do issues. Among the problems studied via neural, fuzzy, neurofuzzy and genetic methodologies are: data fusion, reinforcement learning, approximation properties, multichannel imaging, signal processing, system optimization, gaming, and several forms of control.The book can serve as a reference for researchers and practitioners in the field. Readers can find in it a large amount of useful and timely information, and thus save considerable effort in searching for other scattered literature.Contents:Neural Networks in System Identification and Control:Supervised Learning in Multilayer Perceptrons: The Back-Propagation Algorithm (S G Tzafestas & Y Anthopoulos)Identification of Two-Dimensional State Space Discrete Systems Using Neural Networks (D Wang & A Zilouchian)Neural Networks for Control (R J Mitchell)Neuro-Based Adaptive Regulator (T Tsuji et al.)Local Model Networks and Self-Tuning Predictive Control (P J Gawthrop & E Ronco)Fuzzy and Neuro-Fuzzy Systems in Modeling, Control and Robot Path Planning:An On-Line Self Constructing Fuzzy Modeling Architecture Based on Neural and Fuzzy Concepts and Techniques (S G Tzafestas & K C Zikidis)Neuro-Fuzzy Model Based Control (D Matko et al.)Fuzzy and Neurofuzzy Approaches to Mobile Robot Path and Motion Planning Under Uncertainty (C S Tzafestas & S G Tzafestas)Genetic-Evolutionary Algorithms:A Tutorial Overview of Genetic Algorithms and Their Applications (S G Tzafestas et al.)Results from a Variety of Genetic Algorithm Applications Showing the Robustness of the Approach (W D Potter et al.)Evolutionary Algorithms in Computer-Aided Design of Integrated Circuits (R Drechsler et al.)Soft Computing Applications:Soft Data Fusion (C G Looney & Y Varol)Application of Neural Networks to Computer Gaming (N Baba)Coherent Neural Networks and Their Applications to Control and Signal Processing (A Hirose)Neural, Fuzzy and Evolutionary Reinforcement Learning Systems: An Application Case Study (D A Linkens & H O Nyongesa)Neural Networks in Industrial and Environmental Applications (G C Smith & C L Wrobel)Readership: Researchers and practitioners in systems and control engineering.Key Features:Only book on the Arctic focussing not just on environmental issues, but also on political, economic, energy and military/security issues geared towards the ArcticSignifies the emerging climate change-energy security-conflict nexusPolicy-oriented work designed for decision-makers