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Value Function Approximation in RL by Hadia Ramzan is a document available to read on EtoBox.

What is Value Function Approximation in RL about?

The document outlines a lecture on Value Function Approximation in Reinforcement Learning, covering key topics such as Monte Carlo Learning, Temporal Difference Learning, and Q Learning. It emphasizes the importance of Gradient Descent and Stochastic Gradient Descent in the context of linear value function approximation. Additionally, it discusses the differences between tabular methods and approximation methods, and the use of neural networks as function approximators.

Author

Hadia Ramzan

Language

EN