  The Human visual perception of the world is of a large fixed image that is
highly detailed and sharp. However, receptor density in the retina is not
uniform: a small central region called the fovea is very dense and exhibits
high resolution, whereas a peripheral region around it has much lower spatial
resolution. Thus, contrary to our perception, we are only able to observe a
very small region around the line of sight with high resolution. The perception
of a complete and stable view is aided by an attention mechanism that directs
the eyes to the numerous points of interest within the scene. The eyes move
between these targets in quick, unconscious movements, known as "saccades".
Once a target is centered at the fovea, the eyes fixate for a fraction of a
second while the visual system extracts the necessary information. An
artificial visual system was built based on a fully recurrent neural network
set within a reinforcement learning protocol, and learned to attend to regions
of interest while solving a classification task. The model is consistent with
several experimentally observed phenomena, and suggests novel predictions.
