Collaborative Learning of Hierarchical Task Networks from Demonstration and Instruction

In this work, we focus on advancing the state of the art in intelligent agents that can learn complex procedural tasks from humans. Our main innovation is to view the interaction between the human and the robot as a mixed- initiative collaboration. Our contribution is to integrate hierarchical task networks and collaborative discourse theory into the learning from demonstration paradigm to enable robots to learn complex tasks in collaboration with the human teacher.