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
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.