PATTERNS

Here are some patterns we have identified so far:

The objective problem spaces of many tasks of scientific model building involve searching within matrix spaces, typically subject to conservation conditions or laws, and other constraints; simpler models correspond to matrices of smaller dimensions.
R.E. Valdes-Perez, J.M. Zytkow, and H.A. Simon, ``Scientific Model-Building as Search in Matrix Spaces,'' Proceedings of National Conference on Artificial Intelligence, 1993.
Our recent human/computer discoveries in biology, chemistry, and physics have involved developing new representations of the scientific task, not building expert systems models. This same pattern is conjectured to hold elsewhere.
R.E. Valdes-Perez, ``Some Recent Human/Computer Discoveries in Science and What Accounts for Them,'' AI Magazine, in press.
Many discovery tasks in science are quite specific in the sense that they involve a rather narrow type of inference, but are generic in the sense that they arise in various scientific fields and similar representations and computational approaches serve to automate them in each of the fields. This proposition is grouped under the concept of generic task of scientific discovery.