I may talk about what I read in recent weeks based on the following paper.
Brenna Argall, Sonia Chernova and Manuela Veloso. A Survey of Robot Learning from Demonstration. Robotics and Autonomous Systems. Vol. 57, No. 5, pages 469-483, 2009.
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abstract:
We present a comprehensive survey of robot Learning from Demonstration (LfD), a technique that develops policies from example state to action mappings. We introduce the LfD design choices in terms of demonstrator, problem space, policy derivation and performance, and contribute the foundations for a structure in which to categorize LfD research. Specifically, we analyze and categorize the multiple ways in which examples are gathered, ranging from teleoperation to imitation, as well as the various techniques for policy derivation, including matching functions, dynamics models and plans. To conclude we discuss LfD limitations and related promising areas for future research.
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