Linear Value Function Approximation

By Editorial Team · September 28, 2026 · 7 min read

Linear Value Function Approximation Information Guide

  1. Overview on Linear Value Function Approximation
  2. Key Details
  3. History
  4. Expert Insights
  5. Final Thoughts

Overview on Linear Value Function Approximation

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Key Details

Details RL Course by David Silver - Lecture 6: Value Function Approximation Update
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History

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Lecture 16: Foundations of Reinforcement Learning: General Function Approximation
Lecture 16: Foundations of Reinforcement Learning: General Function Approximation
L8: Value Function Approximation (P6-DQN–basic idea) —Mathematical Foundations of RL
L8: Value Function Approximation (P6-DQN–basic idea) —Mathematical Foundations of RL
5.01 Value Function Approximation
5.01 Value Function Approximation
Provably Efficient Reinforcement Learning with Linear Function Approximation - Chi Jin
Provably Efficient Reinforcement Learning with Linear Function Approximation - Chi Jin
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 5 - Value Function Approximation
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 5 - Value Function Approximation
Introduction to Reinforcement Learning (Lecture 05 - Value Function Approximation) (Part 1)
Introduction to Reinforcement Learning (Lecture 05 - Value Function Approximation) (Part 1)
On The Hardness of Reinforcement Learning With Value-Function Approximation
On The Hardness of Reinforcement Learning With Value-Function Approximation
Finding The Linearization of a Function Using Tangent Line Approximations
Finding The Linearization of a Function Using Tangent Line Approximations
Approximating a Function's Value | Amount of Change and Linear Approximation
Approximating a Function's Value | Amount of Change and Linear Approximation
Linear Approximations | Using Tangent Lines to Approximate Functions
Linear Approximations | Using Tangent Lines to Approximate Functions
DeepMind x UCL RL Lecture Series - Function Approximation [7/13]
DeepMind x UCL RL Lecture Series - Function Approximation [7/13]

Expert Insights

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Last Updated: September 28, 2026

Final Thoughts

Function Approximation | Reinforcement Learning Part 5 Update
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Summary

This video is part of the Udacity course "Reinforcement Learning". Watch the full course at udacity.com/course/ud600. 6:46 How do we choose our target U? 9:27 A Lectures from ECE524 Foundations of Reinforcement Learning at Princeton University, Spring 2024. Recorded Date: 04/04/2024 ... Welcome to the open course “Mathematical Foundations of Reinforcement Learning”. This course provides a mathematical but ... Workshop on Theory of Deep Learning: Where next? Topic: Provably Efficient Reinforcement Learning with For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: stanford.io/ai ... Introduction to Reinforcement Learning (CSC2547 - Spring 2021), Department of Computer Science, University of Toronto. This calculus video tutorial explains how to find the local linearization of a In this video, we discuss how to estimate a Research Scientist Hado van Hasselt explains how to combine deep learning with reinforcement learning for "deep reinforcement ...

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