hf_model_card_template.md

SpaceMining PPO Agent

A PPO agent trained on the SpaceMining Gymnasium environment. This repository includes the final Stable-Baselines3 checkpoint, configuration, and evaluation metrics.

Model Description

• Algorithm: PPO (Stable-Baselines3)
• Environment: SpaceMining (Gymnasium)
• Action Space: Box(3,) — thrust x, thrust y, mine toggle
• Observation Space: Box(53,) — agent state, nearby asteroids (up to 15), mothership relative position

Quickstart

from huggingface_hub import hf_hub_download
from stable_baselines3 import PPO
from space_mining import make_env

ckpt_path = hf_hub_download(repo_id="LUNDECHEN/space-mining-ppo", filename="final_model.zip")
model = PPO.load(ckpt_path)

env = make_env(render_mode='rgb_array')
obs, _ = env.reset()
for _ in range(300):
    # SB3 `predict` may return `(action, state, *extras)` depending on version.
    prediction = model.predict(obs, deterministic=True)
    action = prediction[0] if isinstance(prediction, (tuple, list)) else prediction
    obs, reward, terminated, truncated, info = env.step(action)
    if terminated or truncated:
        break
env.close()

Training Configuration

• See hyperparams.json (algorithm hyperparameters)
• See env_config.json (environment parameters)
• See training_args.json (timesteps, device, versions)

Evaluation

• See evaluation.json

Metric	Value
mean_reward	TBD
std_reward	TBD
episodes	TBD

Agent Behavior

License

• MIT

Authors

• Xinning Zhu (zhuxinning@shu.edu.cn)
• Lunde Chen (lundechen@shu.edu.cn)