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information distance : ウィキペディア英語版
information distance
Information distance is the distance between two finite objects (represented as computer files) expressed as the number of bits in the shortest program which transforms one object into the other one or vice versa on a
universal computer. This is an extension of Kolmogorov complexity.〔(A.N. Kolmogorov, Three approaches to the quantitative definition of information, Problems Inform. Transmission, 1:1(1965), 1–7 )〕 The Kolmogorov complexity of a ''single'' finite object is the information in that object; the information distance between a ''pair'' of finite objects is the minimum information required to go from one object to the other or vice versa.
Information distance was first defined and investigated in 〔(M. Li, P.M.B. Vitanyi, Theory of Thermodynamics of Computation, Proc. IEEE Physics of Computation Workshop, Dallas, Texas, USA, 1992, 42–46 )〕 based on thermodynamic principles, see also.〔(M. Li, P.M.B. Vitanyi, Reversibility and Adiabatic Computation: Trading Time and Space for Energy, Proc. R. Soc. Lond. A 9 April 1996 vol. 452 no. 1947 769–789 )〕 Subsequently it achieved final form in.〔(C.H. Bennett, P. Gacs, M. Li, P.M.B. Vitanyi, W. Zurek, Information distance, IEEE Transactions on Information Theory, 44:4(1998), 1407–1423 )〕 It is applied in the normalized compression distance and the normalized Google distance.
== Properties ==
Formally the information distance ID(x,y) between x and y is defined by
:
ID(x,y) = \min \,

with p a finite binary program for the fixed universal computer
with as inputs finite binary strings x,y. In 〔 it is proven that
ID(x,y) = E(x,y)+O(\log \cdot \max \ ) with
:
E(x,y) = \max \,

where K(\cdot \mid \cdot) is the Kolmogorov complexity defined by 〔 of the prefix type.〔( L.A. Levin, Laws of Information Conservation (Nongrowth) and Aspects of the Foundation of Probability Theory, Problems Inform. Transmission, 10:3(1974), 30–35 )〕 This E(x,y) is the important quantity.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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