CPSC 533V 101 2021W

This course is about learning to control the movement of humans, animals, and robots, with application to character animation, computer vision, robotics, and biological motor control. The bulk of the course will focus on reinforcement learning (RL), which has seen many advances over the past five years. Topics to be covered include motion control problems, sequential decision problems, RL fundamentals, dynamic programming, tabular methods, deep Q-learning, policy gradient methods, common policy gradient algorithms (A2C, A3C, TRPO, PPO), common Q-learning algorithms (DDPG, SAC, TD3), model-based RL and model-predictive control, imitation learning, RL and representation learning, sim-to-real, RL frameworks, forward/inverse kinematics and dynamics, linear quadratic regulators, and advanced topics in RL.