The papers in this volume present theoretical insights and report practical applications both for neural networks, genetic algorithms and evolutionary computation. In the field of natural computing, swarm optimization, bioinformatics and computational biology contributions are no less compelling. A wide selection of contributions report applications of neural networks to process engineering, robotics and control. Contributions also abound in the field of evolutionary computation particularly in combinatorial and optimization problems. Many papers are dedicated to machine learning and heuristics, hybrid intelligent systems and soft computing applications. Some papers are devoted to quantum computation. In addition, kernel based algorithms, able to solve tasks other than classification, represent a revolution in pattern recognition bridging existing gaps. Further topics are intelligent signal processing and computer vision.

From the contents: Neural Networks: Neural Networks Theory
Learning Theory
Computational Neuroscience and Neurodynamics
Neural Networks in Process Engineering
Neural Networks in Robotics and Control
Clustering and Unsupervised Learning
Self-Organising Maps.- Evolutionary Computation: Evolutionary Computation
Genetic Algorithms Theory
Complex Systems and Genetic Programming
Swarm Optimization
Molecular and Quantum Computing.- Adaptive and Natural Computing: BioInformatics and Computational Biology
Adaptive Technology in AI, Natural Computing.- Soft Computing Applications: Machine Learning and Heuristics
Feature Selection and Kernel Methods, Computer Security.- Computer Vision and Pattern Recognition: Computer Vision and Image Processing
Signal Processing and Pattern Recognition.- Hybrid Methods and Tools: Hybrid Intelligent Systems
High Performance and Parallel Computing Tools