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A Framework for Representing Knowledge
It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.Similar feelings seem to be emerging in several centers working on theories of intelligence. They take one form in the proposal of Papert and myself (1972) to sub-structure knowledge into "micro-worlds"; another form in the "Problem-spaces" of Newell and Simon (1972); and yet another in new, large structures that theorists like Schank (1974), Abelson (1974), and Norman (1972) assign to linguistic objects. I see all these as moving away from the traditional attempts both by behavioristic psychologists and by logic-oriented students of Artificial Intelligence in trying to represent knowledge as collections of separate, simple fragments.
I try here to bring together several of these issues by pretending to have a unified, coherent theory. The paper raises more questions than it answers, and I have tried to note the theory's deficiencies.
| Download Paper | |
| Full Title | A Framework for Representing Knowledge |
| Year | 1974 |
| Language | English |
| Book | The Psychology of Computer Vision |
| Keywords | Artificial Intelligence, Psychology, Human-Computer Interaction, Machine Intelligence, Intelligent Interfaces |
| Synonym | Intelligent User Interface |
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