An introduction to genetic algorithms / Melanie Mitchell.

"A Bradford book."

Includes appendices.

Includes bibliographical references (pages 191-201) and index.

1. Genetic Algorithms: An Overview --- 2. Genetic Algorithms in Problem Solving --- 3. Genetic Algorithms in Scientific Models --- 4. Theoretical Foundations of Genetic Algorithms --- 5. Implementing a Genetic Algorithm --- 6. Conclusions and Future Directions.

Also available via the World Wide Web.

"Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics - particularly in machine learning, scientific modeling, and artificial life - and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics."--Publisher description.