• Automatic Task Decomposition and State Abstraction from Demonstration 

      Cobo, Luis C.; Isbell, Charles L., Jr.; Thomaz, Andrea L. (Georgia Institute of TechnologyInternational Foundation for Autonomous Agents and Multiagent Systems, 2012-06)
      Both Learning from Demonstration (LfD) and Reinforcement Learning (RL) are popular approaches for building decision-making agents. LfD applies supervised learning to a set of human demonstrations to infer and imitate the ...
    • Effective robot task learning by focusing on task-relevant objects 

      Lee, Kyu Hwa; Lee, Jinhan; Thomaz, Andrea L.; Bobick, Aaron F. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2009-10)
      In a robot learning from demonstration framework involving environments with many objects, one of the key problems is to decide which objects are relevant to a given task. In this paper, we analyze this problem and propose ...
    • Keyframe-based Learning from Demonstration Method and Evaluation 

      Akgun, Baris; Cakmak, Maya; Jiang, Karl; Thomaz, Andrea L. (Georgia Institute of TechnologySpringer, 2012-06)
      We present a framework for learning skills from novel types of demonstrations that have been shown to be desirable from a human-robot interaction perspective. Our approach –Keyframe-based Learning from Demonstration (KLfD)– ...
    • Trajectories and Keyframes for Kinesthetic Teaching: A Human-Robot Interaction Perspective 

      Akgun, Baris; Cakmak, Maya; Yoo, Jae Wook; Thomaz, Andrea L. (Georgia Institute of Technology, 2012-03)
      Kinesthetic teaching is an approach to providing demonstrations to a robot in Learning from Demonstration whereby a human physically guides a robot to perform a skill. In the common usage of kinesthetic teaching, the robot's ...