Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, criminal investigation, telecommunication networks, and intelligent robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own. A CD-ROM containing the simulations is supplied with the book, to enable interested readers to develop their own application programs with the supplied C/ C++ toolbox.

An Introduction to Computational Intelligence.- Fuzzy Sets and Relations.- Fuzzy Logic and Approximate Reasoning.- Fuzzy Logic in Process Control.- Fuzzy Pattern Recognition.- Fuzzy Databases and Possibilistic Reasoning.- Introduction to Machine Learning Using Neural Nets.- Supervised Neural Learning Algorithms.- Unsupervised Neural Learning Algorithms.- Competitive Learning Using Neural Nets.- Neuro-dynamic Programming by Reinforcement Learning.- Evolutionary Computing Algorithms.- Probabilistic Reasoning and Belief Networks.- Reasoning with Fuzzy Petri Nets.- Image Matching Using Fuzzy Moment Descriptors.- Synergism of Soft Computing Tools.- Object Recognition from Gray Images Using Fuzzy ADALINE Neurons.- Machine Learning Using Fuzzy Petri Nets.- Distributed Machine Learning Using Fuzzy Cognitive Maps.- Computational Intelligence in Tele-Communication Networks.- Computational Intelligence in Mobile Robotics.- Emerging Areas of Computational Intelligence.- Rough Sets, Chaos Theory, Artificial Life, Immunity Network Computing and Multi-Agent Systems.