  Navigating through a visual maze relies on the strategic use of eye movements
to select and identify the route. When navigating the maze, there are
trade-offs between exploring to the environment and relying on memory. This
study examined strategies used to navigating through novel and familiar mazes
that were viewed from above and traversed by a mouse cursor. Eye and mouse
movements revealed two modes that almost never occurred concurrently:
exploration and guidance. Analyses showed that people learned mazes and were
able to devise and carry out complex, multi-faceted strategies that traded-off
visual exploration against active motor performance. These strategies took into
account available visual information, memory, confidence, the estimated cost in
time for exploration, and idiosyncratic tolerance for error. Understanding the
strategies humans used for maze solving is valuable for applications in
cognitive neuroscience as well as in AI, robotics and human-robot interactions.
