Curriculum-Based Deep Reinforcement Learning for Adaptive Robotics: A Mini-Review

Abstract

To facilitate the current and future automation needs, the research community constantly seeks to develop dynamic and efficient autonomous decision-making agents. These agents must not only be robust to modeling uncertainties, internal and external changes, but can adapt to a range of tasks also. Recent progress in deep reinforcement learning has corroborated to its potential to train such autonomous and robust agents.