This clearly structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. It provides authoritative insight into all that is necessary for the successful application of CI methods, describing fundamental concepts and their practical implementations, and explaining the theoretical background underpinning proposed solutions to common problems. Only a basic knowledge of mathematics is required.

Features include electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools; numerous examples and definitions throughout the text; self-contained discussions on artificial neural networks, evolutionary algorithms, fuzzy systems, and Bayesian networks; and coverage of the latest approaches, including ant colony optimization and probabilistic graphical models.