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Returns, Value functions and MDPs
Connection to MDPs
Markov Decision Processes (MDP) Explained: Fundamentals, Expected Return, Policy & Value Functions
Lecture 17 - MDPs & Value/Policy Iteration | Stanford CS229: Machine Learning Andrew Ng (Autumn2018)
Markov Decision Processes 1 - Value Iteration | Stanford CS221: AI (Autumn 2019)
ECE493 - Sections 3.5 to 3.6 - MDP Value Functions
Using Optimal Value Functions to Get Optimal Policies - Fundamentals of Reinforcement Learning
Markov Decision Processes - Computerphile
Model Based Reinforcement Learning: Policy Iteration, Value Iteration, and Dynamic Programming
UofT RL Course - Lecture 12: Value Function Calculation via MDPs -- Naive Approach
Mastering MDPs: Understanding Optimal Values V* and Q* Values
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Last Updated: August 14, 2026
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