  To summarize, it is possible to discern an epistemological frame problem, and to distinguish it from a computational counterpart. The epistemological problem is this: How is it possible for holistic, open-ended, context-sensitive relevance to be captured by a set of propositional, language-like representations of the sort used in classical AI?  The computational counterpart to the epistemological problem is this. How could an inference process tractably be confined to just what is relevant, given that relevance is holistic, open-ended, and context-sensitive?