Representation and Extrapolation in Multi-Layer Perceptrons

Abstract

To give an adequate explanation of cognition and perform certain practical tasks connectionist systems must be able to extrapolate. This work has explored the relationship between input representation and extrapolation, using simulations of multi-layer perceptrons trained to model the identity function. It has been discovered that representation has a marked effect on extrapolation.