GitHub - SimonF24/RL_Notes: My notes from reading Reinforcement Learning by Sutton and Barto (second edition) during summer 2020

My notes from reading Reinforcement Learning by Sutton and Barto (second edition) during summer 2020.

Notes are broken out by chapter.

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Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
Chapter 01 - Introduction.pdf		Chapter 01 - Introduction.pdf
Chapter 02 - Multi-armed Bandits.pdf		Chapter 02 - Multi-armed Bandits.pdf
Chapter 03 - Markov Decision Processes.pdf		Chapter 03 - Markov Decision Processes.pdf
Chapter 04 - Dynamic Programming.pdf		Chapter 04 - Dynamic Programming.pdf
Chapter 05 - Monte Carlo Methods.pdf		Chapter 05 - Monte Carlo Methods.pdf
Chapter 06 - Temporal Difference Learning.pdf		Chapter 06 - Temporal Difference Learning.pdf
Chapter 07 - n-step Bootstrapping.pdf		Chapter 07 - n-step Bootstrapping.pdf
Chapter 08 - Tabular Methods.pdf		Chapter 08 - Tabular Methods.pdf
Chapter 09 - On-Policy Prediction with Approximation.pdf		Chapter 09 - On-Policy Prediction with Approximation.pdf
Chapter 10 - On-Policy Control with Approximation.pdf		Chapter 10 - On-Policy Control with Approximation.pdf
Chapter 11 - Off-Policy Methods with Approximation.pdf		Chapter 11 - Off-Policy Methods with Approximation.pdf
Chapter 12 - Eligibility Traces.pdf		Chapter 12 - Eligibility Traces.pdf
Chapter 13 - Policy Gradient Methods.pdf		Chapter 13 - Policy Gradient Methods.pdf
Chapter 14 - Psychology.pdf		Chapter 14 - Psychology.pdf
Chapter 15 - Neuroscience.pdf		Chapter 15 - Neuroscience.pdf
Chapter 16 - Applications and Case Studies.pdf		Chapter 16 - Applications and Case Studies.pdf
Chapter 17 - Frontiers.pdf		Chapter 17 - Frontiers.pdf
LICENSE		LICENSE
README.md		README.md