pythonlessons/Reinforcement_Learning
Collection of reinforcement learning tutorials implementing DQN, PPO, A2C, and A3C agents for game environments.
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This repository provides hands-on tutorials for reinforcement learning algorithms using TensorFlow 2.3.1 and OpenAI Gym environments. It covers classic algorithms including Deep Q-Learning (DQN), Double DQN, Dueling DQN, Policy Gradient, A2C, A3C, and Proximal Policy Optimization (PPO). Each tutorial includes working implementations that train agents to play games like Pong, LunarLander, and BipedalWalker, with visual demonstrations of trained agent gameplay.
Frequently asked
- What is pythonlessons/Reinforcement_Learning?
- Collection of reinforcement learning tutorials implementing DQN, PPO, A2C, and A3C agents for game environments.
- Is Reinforcement_Learning open source?
- Yes — pythonlessons/Reinforcement_Learning is open source, released under the MIT license.
- What language is Reinforcement_Learning written in?
- pythonlessons/Reinforcement_Learning is primarily written in Python.
- How popular is Reinforcement_Learning?
- pythonlessons/Reinforcement_Learning has 412 stars on GitHub.
- Where can I find Reinforcement_Learning?
- pythonlessons/Reinforcement_Learning is on GitHub at https://github.com/pythonlessons/Reinforcement_Learning.