Understanding Deep Q Network Playing Atari Breakout
Exploring Deep Q Network Playing Atari Breakout reveals several interesting facts. Google DeepMind created an artificial intelligence program using
Key Takeaways about Deep Q Network Playing Atari Breakout
- 5 million of frames, 422 best score using Noisy Double Dueling DQN. Link to my github: https://github.com/Denys88/rl_games.
- Globalfuturist.org: Google #DeepMind Deep Q learning playing Atari Breakout
- Following methods presented in the DeepMind paper '
- The code was implemented by Nathan Sprague and can be downloaded from here: https://github.com/spragunr/deep_q_rl It ...
- Training took ~32 hours on an RTX 3060ti (8GB VRAM). I trained DQN for 50 million environment steps using a replay buffer of ...
Detailed Analysis of Deep Q Network Playing Atari Breakout
This was my first project of the summer took me about 3 weeks to implement and train. It was very challenging and time ... This video illustrates the improvement in the performance of DQN over training (i.e. after 100, 200, 400 and 600 episodes). Original EMDQN code: https://github.com/LinZichuan/emdqn. I have changed a small part of the original code in order to break the ...
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