ML Anthology

Deceptive Path-Planning

Peta Masters, Sebastian Sardiña
IJCAI 2017 pp. 4368-4375
doi:10.24963/IJCAI.2017/610 /ijcai/2017/masters2017ijcai-deceptive/

Abstract

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').

PDF IJCAI Semantic Scholar

Cite

Text

Masters and Sardiña. "Deceptive Path-Planning." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/610

Markdown

[Masters and Sardiña. "Deceptive Path-Planning." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/masters2017ijcai-deceptive/) doi:10.24963/IJCAI.2017/610

BibTeX

@inproceedings{masters2017ijcai-deceptive,
  title     = {{Deceptive Path-Planning}},
  author    = {Masters, Peta and Sardiña, Sebastian},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {4368-4375},
  doi       = {10.24963/IJCAI.2017/610},
  url       = {https://mlanthology.org/ijcai/2017/masters2017ijcai-deceptive/}
}