  This paper investigates deception in the context of motion using a simulated
mobile robot. We analyze some previously designed deceptive strategies on a
mobile robot simulator. We then present a novel approach to adaptively choose
target-oriented deceptive trajectories to deceive humans for multiple
interactions. Additionally, we propose a new metric to evaluate deception on
data collected from the users when interacting with the mobile robot simulator.
We performed a user study to test our proposed adaptive deceptive algorithm,
which shows that our algorithm deceives humans even for multiple interactions
and it is more effective than random choice of deceptive strategies.
