The Search for a Search: Measuring the Information Cost of Higher Level Search

被引:11
|
作者
Dembski, William A. [1 ]
Marks, Robert J., II [2 ]
机构
[1] Discovery Inst, Ctr Sci & Culture, Seattle, WA 98104 USA
[2] Baylor Univ, Dept Elect & Comp Engn, Waco, TX 76798 USA
关键词
No Free Lunch Theorems; active information; active entropy; assisted search; endogenous information;
D O I
10.20965/jaciii.2010.p0475
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Needle-in-the-haystack problems look for small targets in large spaces. In such cases, blind search stands no hope of success. Conservation of information dictates any search technique will work, on average, as well as blind search. Success requires an assisted search. But whence the assistance required for a search to be successful? To pose the question this way suggests that successful searches do not emerge spontaneously but need themselves to be discovered via a search. The question then naturally arises whether such a higher-level "search for a search" is any easier than the original search. We prove two results: (1) The Horizontal No Free Lunch Theorem, which shows that average relative performance of searches never exceeds unassisted or blind searches, and (2) The Vertical No Free Lunch Theorem, which shows that the difficulty of searching for a successful search increases exponentially with respect to the minimum allowable active information being sought.
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页码:475 / 486
页数:12
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