Dynamic Programming: Optimal Control

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Related lectures (32)

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Linear Quadratic (LQ) Optimal Control: Proof of Theorem

Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.

Dynamic Programming: Optimal Control

Explores Dynamic Programming for optimal control, focusing on stability, stationary policy, and recursive solutions.

Linear Quadratic Optimal Control: Analysis and Solution

Explores Linear Quadratic optimal control, analyzing cost, and presenting the solution to the FH-LQ problem.

Infinite-Horizon LQ Control: Solution & Example

Explores Infinite-Horizon Linear Quadratic (LQ) optimal control, emphasizing solution methods and practical examples.

Interactive Lecture: Reinforcement Learning

Explores advanced reinforcement learning topics, including policies, value functions, Bellman recursion, and on-policy TD control.

Advanced Machine Learning: Discrete Reinforcement Learning

Introduces the basics of Reinforcement Learning, covering discrete states, actions, policies, value functions, MDPs, and optimal policies.

Nonlinear Model Predictive Control

Explores Nonlinear Model Predictive Control, covering stability, optimality, pitfalls, and examples.

Markov Decision Processes: Foundations of Reinforcement Learning

Covers Markov Decision Processes, their structure, and their role in reinforcement learning.

Stochastic Optimal Control: Martingale Theorem

Explores Stochastic Optimal Control, emphasizing Optimal Consumption and Investment, the Martingale Representation Theorem, and the Verification Theorem.

Asset Selling: Optimal Revenue Policy

Explores asset selling dynamics, optimal revenue policy, acceptance thresholds, and commodity price impact.