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==Fitness landscapes==

==Fitness landscapes==

== 适应度景观 ==

== 适应度地形 ==

[[File:Visualization of two dimensions of a NK fitness landscape.png|thumb|Visualization of two dimensions of a NK fitness landscape. The arrows represent various mutational paths that the population could follow while evolving on the fitness landscape.|链接=Special:FilePath/Visualization_of_two_dimensions_of_a_NK_fitness_landscape.png]]

[[File:Visualization of two dimensions of a NK fitness landscape.png|thumb|Visualization of two dimensions of a NK fitness landscape. The arrows represent various mutational paths that the population could follow while evolving on the fitness landscape.|链接=Special:FilePath/Visualization_of_two_dimensions_of_a_NK_fitness_landscape.png]]

{{main|Fitness landscape}}

{{main|Fitness landscape}}

Kauffman's NK model defines a combinatorial phase space, consisting of every string (chosen from a given alphabet) of length N. For each string in this search space, a scalar value (called the fitness) is defined. If a distance metric is defined between strings, the resulting structure is a landscape.

Kauffman's NK model defines a combinatorial phase space, consisting of every string (chosen from a given alphabet) of length N. For each string in this search space, a scalar value (called the fitness) is defined. If a distance metric is defined between strings, the resulting structure is a landscape.

考夫曼的NK模型定义了一个组合相空间，由长度为N的每一个字符串(从给定的字母表中选择)组成。对于这个搜索空间中的每个字符串，将定义一个标量值(称为适应度)。如果在字符串之间定义了距离度量，那么得到的结构就是一个景观。

考夫曼的NK模型定义了一个组合相空间，由长度为N的每一个字符串(从给定的字母表中选择)组成。对于这个搜索空间中的每个字符串，将定义一个标量值(称为适应度)。如果在字符串之间定义了距离度量，那么得到的结构就是一个地形。

Fitness values are defined according to the specific incarnation of the model, but the key feature of the NK model is that the fitness of a given string <math>S</math> is the sum of contributions from each locus <math>S_i</math> in the string:

Fitness values are defined according to the specific incarnation of the model, but the key feature of the NK model is that the fitness of a given string <math>S</math> is the sum of contributions from each locus <math>S_i</math> in the string: