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Artificial Intelligence systems cannot yet match human abilities to applyknowledge to situations that vary from what they have been programmed for, ortrained for. In visual object recognition methods of inference exploitingtop-down information (from a model) have been shown to be effective forrecognising entities in difficult conditions. Here this type of inference,called `projection', is shown to be a key mechanism to solve the problem ofapplying knowledge to varied or challenging situations, across a range of AIdomains, such as vision, robotics, or language. Finally the relevance ofprojection to tackling the commonsense knowledge problem is discussed.

Projection: A Mechanism for Human-like Reasoning in Artificial Intelligence