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posted 14. September 2002 22:32
Probability, Optimization Theory, and Evolution
Jason Rosenhouse
Perhaps it is not surprising that mathematics has always been popular among anti-evolutionists. Math is unique in its ability to bamboozle a lay audience, making it well-suited to their purposes. William Dembski, of Baylor University, represents the cutting edge in anti-Darwinian mathematics. His bailiwick is probability and information theory, which he fashions into a formidable, but ultimately unsuccessful, weapon.
For years the Holy Grail of optimization theory was the production of an algorithm that would outperform blind search independent of the particular problem to be solved. The “No Free Lunch” (NFL) of Dembski's title refers to a collection of theorems establishing the nonexistence of such an algorithm (Wolpert and Macready 1996 ). Specifically, the average performance of any algorithm over the class of all optimization problems is no better than blind search. It follows that an algorithm is assured of success only when information about the problem is in some way built into it.
http://evol.allenpress.com/evolonline/?request=get-document&issn=0014-3820&volume=056&issue=08&page=1721
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