  Many natural processes rely on optimizing the success ratio of a search
process. We use an experimental setup consisting of a simple online game in
which players have to find a target hidden on a board, to investigate the how
the rounds are influenced by the detection of cues. We focus on the search
duration and the statistics of the trajectories traced on the board. The
experimental data are explained by a family of random-walk-based models and
probabilistic analytical approximations. If no initial information is given to
the players, the search is optimized for cues that cover an intermediate
spatial scale. In addition, initial information about the extension of the cues
results, in general, in faster searches. Finally, strategies used by informed
players turn into non-stationary processes in which the length of each
displacement evolves to show a well-defined characteristic scale that is not
found in non-informed searches.
