Conservation of Information in Coevolutionary Searches
Abstract
A number of papers show that the No Free Lunch theorem does not apply to coevolutionary search. This has been interpreted as meaning that, unlike classical full query searches, coevolutionary searches do not require extensive a priori knowledge about the domain. Alternately, coevolutionary searches can be viewed as providing incomplete information about fitness and differ from standard evolutionary searches where queries provide full fitness information. Knowing the full value of a fitness is better than knowing partial subjacent fitness information. Consequently, coevolution can be viewed as a degradation of search performance in this sense. We demonstrate this in a number of examples drawn from free lunch proofs in the literature. This observation does not diminish the power or utility of the coevolutionary search. Coevolutionary subjacent queries are often required due to the unavailability or expense of a full query. Nevertheless, coevolution does not allow an escape from the necessity of exploiting prior information in search processes and remains bounded by conservation of information in general and the No Free Lunch theorem in particular.Author Biography
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Robert J. Marks II, Evolutionary Computing and Information Theory; Baylor UniversityRobert J. Marks II is a Distinguished Professor of Engineering in the Department of Engineering at Baylor University.
Marks is the recipient of numerous professional awards, including a NASA Tech Brief Award and a best paper award from the American Brachytherapy Society for prostate cancer research. He is Fellow of both IEEE and The Optical Society of America. His consulting activities include Microsoft Corporation, Pacific Gas & Electric, and Boeing Computer Services. His research has been funded by organizations such as the National Science Foundation, General Electric, Southern California Edison, EPRI, the Air Force Office of Scientific Research, the Office of Naval Research, the Whitaker Foundation, Boeing Defense, the National Institutes of Health, The Jet Propulsion Lab, Army Research Office, and NASA.
Professor Marks was awarded the IEEE Outstanding Branch Councilor Award, The IEEE Centennial Medal, the IEEE Neural Networks Society Meritorious Service Award, the IEEE Circuits and Systems Society Golden Jubilee Award and, for 2007, the IEEE CIS Chapter of the IEEE Dallas Section Volunteer of the Year award. He was was named a Distinguished Young Alumnus of Rose-Hulman Institute of Technology, is an inductee into the Texas Tech Electrical Engineering Academy, and in 2007 was awarded the Banned Item of the Year from the Discovery Institute. Dr. Marks served for 17 years as the faculty advisor to the University of Washington's chapter of Campus Crusade for Christ. In 2010, he was listed by CollegeCrunch.com as one of "The 20 Most Brilliant Christian Professors".
Robert J. Marks II has lots and lots of publications. Some of them are really good. Ten of Dr. Marks’ papers have been reproduced in volumes of collections of seminal papers.
Dr. Marks is the author of the books
- Handbook of Fourier Analysis and Its Applications, Oxford University Press -2009,
- Introduction to Shannon Sampling and Interpolation Theory (Springer Verlag, 1991), and
- Neural Smithing : Supervised Learning in Feedforward Artificial Neural Networks (MIT Press, 1999) - with Russ Reed.
He is the editor or co-editor of four other books. More than you want to know about Dr. Marks is on the websites http://RobertMarks.org and http://EvoInfo.org.
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