https://github.com/pegah-ardehkhani/reinforcement-learning-algorithms-from-scratch

Explore key RL algorithms with detailed explanations and fully commented Python code implementations
https://github.com/pegah-ardehkhani/reinforcement-learning-algorithms-from-scratch

reinforcement-learning reinforcement-learning-agent reinforcement-learning-algorithms reinforcement-learning-environments rl

Last synced: 6 months ago
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Explore key RL algorithms with detailed explanations and fully commented Python code implementations

• Host: GitHub
• URL: https://github.com/pegah-ardehkhani/reinforcement-learning-algorithms-from-scratch
• Owner: Pegah-Ardehkhani
• License: mit
• Created: 2024-10-15T20:11:07.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-10-19T12:09:00.000Z (12 months ago)
• Last Synced: 2024-10-19T12:30:09.573Z (12 months ago)
• Topics: reinforcement-learning, reinforcement-learning-agent, reinforcement-learning-algorithms, reinforcement-learning-environments, rl
• Language: Jupyter Notebook
• Homepage:
• Size: 2.04 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Reinforcement Learning Algorithms from Scratch ![license](https://img.shields.io/github/license/Pegah-Ardehkhani/Reinforcement-Learning-Algorithms-from-Scratch.svg)

 

   



## 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. SARSA(λ)**

**12. Q-Learning**

**13. Deep Q-Learning**