Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,48 @@
+---
+license: mit
+tags:
+  - reinforcement-learning
+  - ppo
+  - openfront
+  - game-ai
+---
+
+# OpenFront RL Agent
+
+PPO-trained agent for [OpenFront.io](https://openfront.io), a multiplayer territory control game.
+
+## Training Details
+
+- **Algorithm:** PPO (Proximal Policy Optimization)
+- **Architecture:** Actor-Critic with shared backbone (256→256→128)
+- **Observation dim:** N/A
+- **Max neighbors:** N/A
+- **Maps:** N/A (random per episode)
+- **Opponents:** N/A N/A bots
+- **Parallel envs:** N/A
+- **Learning rate:** N/A
+- **Rollout steps:** N/A
+- **Updates trained:** N/A
+- **Global steps:** N/A
+- **Best mean reward:** N/A
+
+## Final Training Metrics
+
+- **Mean reward:** 29.898164215087892
+- **Mean episode length:** 3657.29
+- **Loss:** 0.8671517372131348
+
+## Usage
+
+```python
+from train import ActorCritic
+import torch
+
+model = ActorCritic(obs_dim=N/A, max_neighbors=N/A)
+model.load_state_dict(torch.load("best_model.pt", weights_only=True))
+model.eval()
+```
+
+## Repository
+
+Trained from [josh-freeman/openfront-rl](https://github.com/josh-freeman/openfront-rl).