One of the key goals of cognitive science is to develop theories that are strongly equivalent with respect to to-be-explained systems. This requires that evidence be collected to defend the claim that the model and the to-be-explained system are carrying out the same procedures to compute a function.
One kind of information that could be used to examine this claim is called error analysis. In an error analysis, one could (for two different systems) rank order problems in terms of their difficulty, as revealed by their likelihood to produce mistakes. This is an example of relative complexity evidence. A more detailed approach would be to classify the nature of the errors that each system made. In either case, if the two systems were strongly equivalent, then we would expect them to produce the same rank orderings of difficulty, and to also produce the same qualitative patterns of errors.
- Pylyshyn, Z.W. (1984). Computation and cognition. Cambridge, MA: MIT Press
(Revised December 2009)