| tags: | |
| - ML-Agents-SnowballTarget | |
| - ml-agents | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - unity-ml-agents | |
| model-index: | |
| - name: ppo-SnowballTarget | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: ML-Agents-SnowballTarget | |
| type: ML-Agents-SnowballTarget | |
| metrics: | |
| - type: mean_reward | |
| value: 25.00 +/- 3.00 | |
| name: mean_reward | |
| verified: false | |
| # PPO Agent playing SnowballTarget (Unity ML-Agents) | |
| This is a trained model of an agent playing **ML-Agents-SnowballTarget** using the **ml-agents** library as part of the [Hugging Face Deep Reinforcement Learning Course](https://huggingface.co/deep-rl-course/en/unit0/introduction). | |
| - **Environment**: ML-Agents-SnowballTarget | |
| - **Library**: ml-agents | |
| - **Mean Reward**: 25.00 +/- 3.00 | |
| - **Student**: plpanjali05 | |
| ## Usage | |
| ```python | |
| # To load this model, refer to the corresponding unit notebook in the Hugging Face Deep RL Course. | |
| ``` | |