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PongNoFrameskip-v4_DQN
Hawk91/PongNoFrameskip-v4_DQN
PongNoFrameskip-v4_DQN is a machine learning model from Hawk91. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is a trained model of DQN agent that plays PongNoFrameskip-v4 Pong is a Atari 2600 game imported from Gym environment. Agent is implemented from Deep Reinforcement Learning by Max Lapan. The code is present in th…
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Updated Aug 21, 2023
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At a glance
- Access
- Public
- Created
- Aug 20, 2023
- Updated
- Aug 21, 2023
- SHA
- 59fcd231
Model card
From the Hugging Face model README
DQN Agent Playing Pong
This is a trained model of DQN agent that plays PongNoFrameskip-v4 Pong is a Atari 2600 game imported from Gym environment. Agent is implemented from Deep Reinforcement Learning by Max Lapan. The code is present in the github link: https://github.com/mohit-ix/DeepRL/tree/main/Unit%206 The performance of agent at different steps is present here: https://youtu.be/03Pl5Odc2jM
To use the agent use "03_dqn_play.py" from the github link and type:
python 03_dqn_play.py -m [model_name] -r [recording_location] --no-vis
Add "-r [recoding_location]" if you want to save the recording and remove "--no-vis" if you want to render the gamplay by the agent.
- Created
- Aug 20, 2023
- Updated
- Aug 21, 2023