Updated: README.md

README.md

@@ -3,11 +3,32 @@ license: mit
 language:
   - en
 tags:
-  - reinforcement learning
-  - games
+  - 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
+# **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>
+```