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---
license: mit
language:
- en
tags:
- Atari-Breakout-v0
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: Deep Q Learning
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Atari-Breakout-v0
type: Atari-Breakout-v0
metrics:
- type: mean_reward
value: 29.00
name: mean_reward
verified: false
---
# **Deep Q-Learning based Agent for Atari Breakout**
The agent showcased in this space is trained using the Deep Q-Learning algorithm.
The agent was trained for $3500$ episodes with a learning rate of $0.00001$ and an epsilon value that decreased linearly over time.
## Usage
```bash
python main.py --model_folder <Name of the folder> --model_name <Name of the model> --save_video 1 --video_name <Name of the video file>
```
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