  The paper focuses on the problem of learning saccades enabling visual object
search. The developed system combines reinforcement learning with a neural
network for learning to predict the possible outcomes of its actions. We
validated the solution in three types of environment consisting of
(pseudo)-randomly generated matrices of digits. The experimental verification
is followed by the discussion regarding elements required by systems mimicking
the fovea movement and possible further research directions.
