Applying Ant Colony Optimization algorithms for high-level behavior learning and reproduction from demonstrations

摘要

In domains where robots carry out human's tasks, the ability to learn new behaviors easily and quickly plays an important role. Two major challenges with Learning from Demonstration (LfD) are to identify what information in a demonstrated behavior requires attention by the robot, and to generalize the learned behavior such that the robot is able to perform the same behavior in novel situations.