Electrical Engineering and Computer Science
Lecture 1: Introduction
Lecture 2: The Simple Pendulum
Lecture 3: Optimal Control of the Double Integrator
Lecture 4: Optimal Control of the Double Integrator (cont.)
Lecture 5: Numerical Optimal Control (Dynamic Programming)
Lecture 6: Acrobot and Cart-pole
Lecture 7: Swing-up Control of Acrobot and Cart-pole Systems
Lecture 8: Dynamic Programming (DP) and Policy Search
Lecture 9: Trajectory Optimization
Lecture 10: Trajectory Stabilization and Iterative Linear Quadratic Regulator
Lecture 11: Walking
Lecture 12: Walking (cont.)
Lecture 13: Running
Lecture 14: Feasible Motion Planning
Lecture 15: Global Policies from Local Policies
Lecture 16: Introducing Stochastic Optimal Control
Lecture 17: Stochastic Gradient Descent
Lecture 18: Stochastic Gradient Descent 2
Lecture 19: Temporal Difference Learning
Lecture 20: Temporal Difference Learning with Function Approximation
Lecture 21: Policy Improvement
Lecture 22: Actor-critic Methods
Lecture 23: Case Studies in Computational Underactuated Control
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