The new experimentalism, a development in the modern philosophy of science, considers that an experiment can have a life of its own. This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples. Summarizing results from the author's consulting to industry and his experience teaching university courses and conducting tutorials at international conferences, is suitable for practitioners and researchers and also for lecturers and students. The text is supplemented online with downloads and exercises.

There are no directly competing books that combine modern statistical approaches and evolutionary computing approaches in the design of experiments and the solution to optimization problems, and the author is very well positioned to address this gap given his background in industrial research on evolutionary computing applications, a corresponding academic research position, and corresponding teaching experience. He has run the tutorial directly relevant to this topic at the main conference in the field, and will do so again in 2006. Includes supplementary material: sn.pub/extras

Autorentext

Sandor Markon has 25 years experience as a designer, researcher and manager dealing with control systems with major elevator manufacturers. He is also active in publishing papers and abstracts in related fields. He has been involved in the installation of four generations of elevator systems in buildings world-wide. The current volume would gathers that knowledge together with that of other researchers currently scattered in short articles, patent disclosures, etc., into one place.

Inhalt
Basics.- Research in Evolutionary Computation.- The New Experimentalism.- Statistics for Computer Experiments.- Optimization Problems.- Designs for Computer Experiments.- Search Algorithms.- Results and Perspectives.- Comparison.- Understanding Performance.- Summary and Outlook.