##
Complexity and Scientific Modelling

**CPM Report No.: 97-23**

*By: Bruce Edmonds
*

Date: April 1997
**Presented at:** 20th International Wittgenstein Symposium, Kirchberg am Wechsel, Austria, August 1997.

Published as: Edmonds, B. (2000). Complexity and Scientific Modelling. Foundations of Science. 5: 379-390

##
Abstract

There have been many attempts at formulating measures of complexity of
physical processes. Here we reject this direct approach and attribute complexity
only to models of these processes in a given language, to reflect its "difficulty".
A framework for modelling is outlined which includes the language of modelling,
the complexity of models in that language, the error in the model's predictions
and the specificity of the model.
Many previous formulations of complexity can be seen as either: a special
case of this framework; attempts to "objectify" complexity by considering
only minimally complex models or its asymptotic behaviour; relativising
it to a fixed mathematical structure in the absence of noise; misnamed
in that they capture the specificity rather than the complexity.

Such a framework makes sense of a number of aspects of scientific modelling.
Complexity does not necessarily correspond to a lack of *simplicity *or
lie between order and disorder. When modelling is done by agents with severe
resource limitations, the acceptable trade-offs between complexity, error
and specificity can determine the effective relations between these. The
characterisation of noise will emerge from this. Simpler theories are not
a priori more likely to be correct but sometimes preferring the simpler
theory at the expense of accuracy can be a useful heuristic.

*Access as:*

**| BE Home | Other CPM
Reports | CPM home page |**