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.
- Original EMDQN code: https://github.com/LinZichuan/emdqn. I have changed a small part of the original code in order to break the ...
- Following methods presented in the DeepMind paper '
- Q
- The code was implemented by Nathan Sprague and can be downloaded from here: https://github.com/spragunr/deep_q_rl It ...
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 ... Globalfuturist.org: Google #DeepMind Deep Q learning playing Atari Breakout Training took ~32 hours on an RTX 3060ti (8GB VRAM). I trained DQN for 50 million environment steps using a replay buffer of ...
This video illustrates the improvement in the performance of DQN over training (i.e. after 100, 200, 400 and 600 episodes).
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