Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative Tasks

@article{Gao2020JointMM,
  title={Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative Tasks},
  author={Xiaofeng Gao and R. Gong and Yizhou Zhao and Shu Wang and Tianmin Shu and Song-Chun Zhu},
  journal={2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
  year={2020},
  pages={1119-1126}
}
  • Xiaofeng Gao, R. Gong, Song-Chun Zhu
  • Published 24 July 2020
  • Computer Science
  • 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
Human collaborators can effectively communicate with their partners to finish a common task by inferring each other’s mental states (e.g., goals, beliefs, and desires). Such mind-aware communication minimizes the discrepancy among collaborators’ mental states, and is crucial to the success in human ad-hoc teaming. We believe that robots collaborating with human users should demonstrate similar pedagogic behavior. Thus, in this paper, we propose a novel explainable AI (XAI) framework for… 

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