Confidence-Based Robot Policy Learning from Demonstration

@inproceedings{Chernova2009ConfidenceBasedRP,
  title={Confidence-Based Robot Policy Learning from Demonstration},
  author={Sonia Chernova},
  year={2009}
}
The problem of learning a policy, a task representation mapping from world states to actions, lies at the heart of many robotic applications. One approach to acquiring a task policy is learning from demonstration, an interactive technique in which a robot learns a policy based on example state to action mappings provided by a human teacher. This thesis introduces Confidence-Based Autonomy, a mixed-initiative single robot demonstration learning algorithm that enables the robot and teacher to… CONTINUE READING

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