RL Math

These notes are based on Mathematical Foundations of Reinforcement Learning by Shiyu Zhao.

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Prerequisites: Basic Concepts in RL: Markov Decision Processes, State, Action, Reward, Policy, Transition Probability, \(\gamma\), Trajectory, Return. Episodes.

1. Chapter 2: State Values and Bellman Equation
2. Chapter 3: Optimal State Values and Bellman Optimality Equation
3. Chapter 4: Value Iteration and Policy Iteration
4. Chapter 5: Monte Carlo Methods