README.md

metadata

tags:
  - ppo
  - reinforcement-learning
  - swarm
  - drone
  - bittensor
license: mit
language:
  - en
library_name: stable-baselines3

🚀 Swarm PPO Drone

This repository contains a Proximal Policy Optimization (PPO) model trained for swarm/drone control.
The model was trained using Gymnasium environments with Stable-Baselines3 and exported for use in Bittensor Subnet 124 (Swarm).

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📂 Files

• policy.pth – Trained PPO policy weights (PyTorch).
• ppo_policy.zip – Stable-Baselines3 PPO saved model (reload with PPO.load()).
• safe_policy_meta.json – Metadata for policy compliance.
• best/ – Best checkpointed model during training.
• eval_logs/ – Evaluation logs.
• tb_logs/ – TensorBoard logs.

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🛠️ Usage

Load with Stable-Baselines3

from stable_baselines3 import PPO
import gymnasium as gym

# Load model
model = PPO.load("ppo_policy.zip")

# Example run
env = gym.make("CartPole-v1")
obs, _ = env.reset()
action, _ = model.predict(obs)
print("Predicted action:", action)