Peta Masters, Sebastian Sardina
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 4368-4375. https://doi.org/10.24963/ijcai.2017/610
Deceptive path-planning involves finding a path such that the probability of an observer identifying the path's final destination - before it has been reached - is minimised. This paper formalises deception as it applies to path-planning and introduces the notion of a last deceptive point (LDP) which, when measured in terms of 'path completion', can be used to rank paths by their potential to deceive. Building on recent developments in probabilistic goal-recognition, we propose a formula to calculate an optimal LDP and present strategies for the generation of deceptive paths by both simulation ('showing the false') and dissimulation ('hiding the real').
Planning and Scheduling: Activity and Plan Recognition
Planning and Scheduling: Model-Based Reasoning
Robotics and Vision: Motion and Path Planning