Unpacking Human Teachers’ Intentions for Natural Interactive Task Learning

@article{Ramaraj2021UnpackingHT,
  title={Unpacking Human Teachers’ Intentions for Natural Interactive Task Learning},
  author={Preeti Ramaraj and Charlie Ortiz and Matthew Evans Klenk and Shiwali Mohan},
  journal={2021 30th IEEE International Conference on Robot \& Human Interactive Communication (RO-MAN)},
  year={2021},
  pages={1173-1180}
}
  • P. Ramaraj, C. Ortiz, +1 author Shiwali Mohan
  • Published 12 February 2021
  • Computer Science
  • 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)
Interactive Task Learning (ITL) is an emerging research agenda that studies the design of complex intelligent robots that can acquire new knowledge through natural human teacher-robot learner interactions. ITL methods are particularly useful for designing intelligent robots whose behavior can be adapted by humans collaborating with them. Various research communities are contributing methods for ITL and a large subset of this research is robot-centered with a focus on developing algorithms that… 

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