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README.md
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value: '19'
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name: mean_reward
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verified: false
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value: '19'
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name: mean_reward
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verified: false
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---
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# **DQN** Agent Playing **Pong**
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This is a trained model of **DQN** agent that plays **PongNoFrameskip-v4**
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Pong is a Atari 2600 game imported from Gym environment.
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Agent is implemented from Deep Reinforcement Learning by Max Lapan.
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The code is present in the github link: [https://github.com/mohit-ix/DeepRL/tree/main/Unit%206]
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The performance of agent at different steps is present here: [https://youtu.be/03Pl5Odc2jM]
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To use the agent use "03_dqn_play.py" from the github link and type:
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```python
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python 03_dqn_play.py -m [model_name] -r [recording_location] --no-vis
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```
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add "-r [recoding_location]" if you want to save the recording
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remove "--no-vis" if you want to render the gamplay by the agent.
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