Proceedings of the Annual Meeting of the Cognitive Science Society

The effort within AI to improve the robustness of expert systems has led to increasing interest in "deep" reasoning, which is representing and reasoning about the knowledge that underlies the compiled knowledge of expert systems. One view is that deep reasoning is the same as causal reasoning. Our aim in this paper is to show that this view is naive, specifically that certain kinds of causal models omit mioTinat\ou that is crucial to understanding the causality within a physical situation. Our conclusion is that "deepness" is relative to the phenomena of interest.I.e. whether the representation describes the properties and relationships that mediate interactions among the phenomena and whether the reasoning processes take this information into account.