International Symposium on Neural Networks 2006

Computational Intelligence: A Free Source of Information?

Department of Engineering

Baylor University, Waco,Texas, USA

Abstract
Engineers use models of science to improve quality of life. Computational intelligence is such a useful engineering tool. It can create unexpected, insightful and clever results. Consequently, an image is often painted of computational intelligence as a free source of information. Although fast computers performing search do add information to a design, the needed information to solve even moderately sized problems is beyond the computational ability of the closed universe. Assumptions concerning the solution must be included. Generally, artificial intelligence offers this information explicitly while computational intelligence does so implicitly. For targeted search, the requirement for added information is well known. The need has been popularized in the last decade by the No Free Lunch theorems [3,5]. Using classic information theory [2,4], we claim the added information for searches can, indeed, be measured. The total information available prior to search is determined by application of Bernoulli's principle of insufficient reason [1]. The added information measures the information provided by the evolutionary program towards achieving the available information. If the values are equal, the search is assured to result in a success. Some recently proposed evolutionary models are shown, surprisingly, to offer negative added information to the design process and therefore perform worse than random sampling.

[1] Jakob Bernoulli, "Ars Conjectandi" ("The Art of Conjecturing"), (1713).
[2] Cover & Thomas, Elements of Information Theory, Wiley-Interscience, 1991.
[3] Yu-Chi Ho and D.L. Pepyne, "Simple explanation of the No Free Lunch Theorem", Proceedings of the 40th IEEE Conference on Decision and Control, Orlando, Florida, (2001).
[4] A. Papoulis, Probability, Random Variables and Stochastic Processes, McGraw Hill, 1991.
[5] David Wolpert, William G. Macready, "No free lunch theorems for optimization", IEEE Trans. Evolutionary Computation 1(1): 67-82 (1997).

Biosketch
     Robert J. Marks II, Ph.D., is Distinguished Professor of Engineering and Graduate Director in the Department of Engineering at Baylor University. He is Fellow of both IEEE and The Optical Society of America.
    Professor Marks was awarded the Outstanding Branch Councilor award by IEEE and was presented with the IEEE Centennial Medal. He was named a Distinguished Young Alumnus of Rose-Hulman Institute of Technology and is an inductee into the Texas Tech Electrical Engineering Academy. He was awarded the Golden Jubilee Award by the IEEE Circuits and Systems Society. He is also the first recipient of the IEEE Neural Networks Society Meritorious Service Award and the first honorary member of the Puget Sound Section of the Optical Society of America. Recently, he was a recipient of a NASA Tech Brief Award and has received a best paper award at the American Brachytherapy Society 23rd Annual Meeting.
    Dr. Marks served as a Distinguished Lecturer for the IEEE Computational Intelligence Society (CIS).
     Dr. Marks was Chair of IEEE Neural Networks Committee and served as the first President of the IEEE Neural Networks Council (now the IEEE CIS Society). He was given the honorary title of Charter President. He served a six year stint of the Editor-in-Chief of the IEEE Transactions on Neural Networks and as an Associate Editor of the IEEE Transactions on Fuzzy Systems.
     Dr. Marks has over 300 publications. Some of them are very good. Ten of Dr. Marks’ papers have been reproduced in volumes of collections of outstanding papers. He has three US patents in the field of artificial neural networks and signal processing.
    Dr. Marks is the author and co-author of the books
    * Introduction to Shannon Sampling and Interpolation Theory (Springer Verlag, 1991), and
    * Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (MIT Press, 1999) respectively, and is editor of
    * Advanced Topics in Shannon Sampling and Interpolation Theory (Springer Verlag, 1993), and
    * Fuzzy Logic Technology and Applications, (IEEE Technical Activities Board, Piscataway, 1994). He is also a co-editor of the volumes
    * Computational Intelligence: Imitating Life, (IEEE Press, 1994), and
    * Computational Intelligence: A Dynamic Systems Perspective, (IEEE Press, 1995).