Introduction to Evolutionary Computing (Natural Computing Series)

Rating:
Summary: Excellent introduction
Review: I taught our introduction to evolutionary computation class from this book. It is a well rounded introduction to the topic covering most of the introductorty material you would expect. There is an real dearth of good introductory books for EC. This is probably the best because of its breadth. Its weakness is its lack of detail. It would not hurt if they covered the same material in about 50% more pages. As soon as they start a topic its over and on to the next topic. But if you are new to the field they give plenty of references and touch on most topics in enough detail for students to implement. All in all a good solid job.

Rating:
Summary: an excellent introduction
Review: The book is easy and refreshing to read. Assuming only a minimum of prior knowledge, all the relevant aspects are covered. The focus is on practical applications, with numerous examples, simple equations and plenty of practical advise for the user.

As should be the costum with every scientific introduction, the authors are at great pains to clarify the relationship between the different flavours of EC and to show how they historically developed.

The book does not provide much on the mathematical level, though. Not even a basic graph theoretical analysis of mutation and recombination.

This said, the book is still perfect to get you started.

Rating:
Summary: An excellent textbook suitable for all levels
Review: This is an excellent textbook which covers most aspects of the Evolutionary Computing. It's suitable for all levels. It's easy to follow, rich in content and has many references (439 to be precise) for further information. The table of contents from the book's web site is as follows:

1. Introduction
2. What is an Evolutionary Algorithm?
3. Genetic Algorithms
4. Evolution Strategies
5. Evolutionary Programming
6. Genetic Programming
7. Learning Classifier Systems
8. Parameter Control in Evolutionary Algorithms
9. Multi-Modal Problems and Spatial Distribution
10. Hybridisation with Other Techniques: Memetic Algorithms
11. Theory
12. Constraint Handling
13. Special Forms of Evolution
14. Working with Evolutionary Algorithms
15. Summary
16. Appendices
17. Index
18. References

Recommended to everyone interested in EC.