Complexity and scientific modelling

Foundations of Science 5 (3):379-390 (2000)
It is argued that complexity is not attributable directly to systems or processes but rather to the descriptions of their `best' models, to reflect their difficulty. Thus it is relative to the modelling language and type of difficulty. This approach to complexity is situated in a model of modelling. Such an approach makes sense of a number of aspects of scientific modelling: complexity is not situated between order and disorder; noise can be explicated by approaches to excess modelling error; and simplicity is not truth indicative but a useful heuristic when models are produced by a being with a tendency to elaborate in the face of error.
Keywords complexity  learning  modelling  noise  simplicity
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DOI 10.1023/A:1011383422394
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