Evolution Intelligence

Offering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research.

Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques has been growing in the last decade, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science.

The reader first receives a comprehensive overview of the development and complex techniques of AI in an easy-to-understand presentation. Then, with a wink, all areas of application of AI are described in detail with the most current examples - critically evaluating, so that the reader may feel AI-firm. At the end of the book the author alerts the reader with imaginative future scenarios in an amusing way, what breathtaking perspectives are connected with AI in the sense of evolution.