Game-Theoretic Modeling of Human Adaptation in Human-Robot Collaboration

@article{Nikolaidis2017GameTheoreticMO,
  title={Game-Theoretic Modeling of Human Adaptation in Human-Robot Collaboration},
  author={Stefanos Nikolaidis and Swaprava Nath and Ariel D. Procaccia and Siddhartha S. Srinivasa},
  journal={2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI},
  year={2017},
  pages={323-331}
}
In human-robot teams, humans often start with an inaccurate model of the robot capabilities. As they interact with the robot, they infer the robot's capabilities and partially adapt to the robot, i.e., they might change their actions based on the observed outcomes and the robot's actions, without replicating the robot's policy. We present a game-theoretic model of human partial adaptation to the robot, where the human responds to the robot's actions by maximizing a reward function that changes… CONTINUE READING
Highly Cited
This paper has 23 citations. REVIEW CITATIONS
Related Discussions
This paper has been referenced on Twitter 6 times. VIEW TWEETS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction

2018 IEEE International Conference on Robotics and Automation (ICRA) • 2018
View 2 Excerpts

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…