Lecture 1: Introduction

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Lecture 2: The Simple Pendulum

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Lecture 3: Optimal Control of the Double Integrator

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Lecture 4: Optimal Control of the Double Integrator (cont.)

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Lecture 5: Numerical Optimal Control (Dynamic Programming)

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Lecture 6: Acrobot and Cart-pole

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Lecture 7: Swing-up Control of Acrobot and Cart-pole Systems

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Lecture 8: Dynamic Programming (DP) and Policy Search

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Lecture 9: Trajectory Optimization

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Lecture 10: Trajectory Stabilization and Iterative Linear Quadratic Regulator

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Lecture 11: Walking

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Lecture 12: Walking (cont.)

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Lecture 13: Running

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Lecture 14: Feasible Motion Planning

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Lecture 15: Global Policies from Local Policies

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Lecture 16: Introducing Stochastic Optimal Control

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Lecture 17: Stochastic Gradient Descent

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Lecture 18: Stochastic Gradient Descent 2

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Lecture 19: Temporal Difference Learning

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Lecture 20: Temporal Difference Learning with Function Approximation

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Lecture 21: Policy Improvement

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Lecture 22: Actor-critic Methods

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Lecture 23: Case Studies in Computational Underactuated Control

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