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Shimon Edelman, Nathan Intrator
In visual perception, learning is a pervasive phenomenon which, when properly studied, may offer valuable insights into the inner workings of the brain. We outline a theoretical framework for the computational study of perceptual learning, aiming to make the relationships among the existing models more readily apparent, and to identify promising directions for future research.