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Explore key RL algorithms with detailed explanations and fully commented Python code implementations

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Name		Name	Last commit message	Last commit date
Latest commit History 120 Commits
01. Epsilon Greedy		01. Epsilon Greedy
02. Optimistic Initial Values		02. Optimistic Initial Values
03. UCB1		03. UCB1
04. Bayesian Bandit Thompson Sampling		04. Bayesian Bandit Thompson Sampling
05. Iterative Policy Evaluation		05. Iterative Policy Evaluation
06. Policy Iteration		06. Policy Iteration
07. Value Iteration		07. Value Iteration
08. Monte Carlo		08. Monte Carlo
08. TD(0)		08. TD(0)
09. TD(λ)		09. TD(λ)
10. SARSA		10. SARSA
11. Q-Learning		11. Q-Learning
12. Deep Q-Learning		12. Deep Q-Learning
LICENSE		LICENSE
README.md		README.md

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Reinforcement Learning Algorithms from Scratch

Table of content ✍️

01. Epsilon Greedy

02. Optimistic Initial Values

03. UCB1

04. Bayesian Bandit Thompson Sampling

05. Iterative Policy Evaluation

06. Policy Iteration

07. Value Iteration

08. TD(0)

09. TD(λ)

10. SARSA

11. Q-Learning

12. Deep Q-Learning