Update README.md

README.md

@@ -7,31 +7,39 @@ tags:
 - ML-Agents-SoccerTwos
 ---
 
-  # **poca** Agent playing **SoccerTwos**
-  This is a trained model of a **poca** agent playing **SoccerTwos**
-  using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
-  
-  To see full code, visit: https://www.kaggle.com/code/syedjarullahhisham/drl-huggingface-unit-7-marl-soccer-2vs2
-
-  ## Usage (with ML-Agents)
-  The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
-
-  We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
-  - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
-  browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
-  - A *longer tutorial* to understand how works ML-Agents:
-  https://huggingface.co/learn/deep-rl-course/unit5/introduction
-
-  ### Resume the training
-  ```bash
-  mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
-  ```
-
-  ### Watch your Agent play
-  You can watch your agent **playing directly in your browser**
-
-  1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
-  2. Step 1: Find your model_id: hishamcse/poca-SoccerTwos
-  3. Step 2: Select your *.nn /*.onnx file
-  4. Click on Watch the agent play 👀
+# **poca** Agent playing **SoccerTwos**
+This is a trained model of a **poca** agent playing **SoccerTwos**
+using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
+
+## Codes
+
+Github repos(Give a star if found useful):
+  * https://github.com/hishamcse/Advanced-DRL-Renegades-Game-Bots
+  * https://github.com/hishamcse/DRL-Renegades-Game-Bots
+
+Kaggle Notebook:
+  * https://www.kaggle.com/code/syedjarullahhisham/drl-huggingface-unit-7-marl-soccer-2vs2
+
+
+## Usage (with ML-Agents)
+The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
+
+We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
+- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
+browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
+- A *longer tutorial* to understand how works ML-Agents:
+https://huggingface.co/learn/deep-rl-course/unit5/introduction
+
+### Resume the training
+```bash
+mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
+```
+
+### Watch your Agent play
+You can watch your agent **playing directly in your browser**
+
+1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
+2. Step 1: Find your model_id: hishamcse/poca-SoccerTwos
+3. Step 2: Select your *.nn /*.onnx file
+4. Click on Watch the agent play 👀