Computational intelligence is a well-established paradigm, where new theories with asound biological understanding have been evolving. The current experimental systemshave many of the characteristics of biological computers (brains in other words) and arebeginning to be built to perform a variety of tasks that are difficult or impossible to dowith conventional computers. As evident, the ultimate achievement in this field wouldbe to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17chapters offers a step-by-step introduction (in a chronological order) to the variousmodern computational intelligence tools used in practical problem solving. Staring withdifferent search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligenttechniques; the authors illustrate the design of knowledge-based systems and advancedexpert systems, which incorporate uncertainty and fuzziness. Machine learning algorithmsincluding decision trees and artificial neural networks are presented and finally thefundamentals of hybrid intelligent systems are also depicted.Academics, scientists as well as engineers engaged in research, development andapplication of computational intelligence techniques, machine learning and data miningwould find the comprehensive coverage of this book invaluabl