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Reinforcement Learning 5: Function Approximation and Deep Reinforcement Learning
Reinforcement Learning using Function Approximation
On The Hardness of Reinforcement Learning With Value-Function Approximation
Approximation Theory Explained | Neural Network Expressivity & Function Approx. in AI | Lec No 30
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation
Function Approximation and Eligibility Traces
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 5 - Value Function Approximation
5.01 Value Function Approximation
Eric Mazumdar - Provably Convergent Independent Learning w/ Function Approximation in Competitive RL
L8: Value Function Approximation (P6-DQN–basic idea) —Mathematical Foundations of RL
UofT RL Course - Lecture 39: Learning Action-Value via Function Approximation
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Last Updated: August 14, 2026
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