README.md

🚀 Snapshot Reinforcement Learning: Leveraging Prior Trajectories for Efficiency

This repository contains the code for the paper "Snapshot Reinforcement Learning: Leveraging Prior Trajectories for Efficiency" by Yanxiao Zhao, Yangge Qian, Tianyi Wang, Jingyang Shan, Xiaolin Qin.

Running the code

The code is written in Python 3.9 and PyTorch 2.0.1. To install the required dependencies, run

pip install -r src/requirements.txt

To train the agents, run the following commands:

# for S3RL+TD3
python src/snapshot_td3_mujoco.py --env-id Hopper-v4 --n-clusters 6 --truncate-step 100 --seed 1

# for SnapshotRL+SC+TD3
python src/snapshot_td3_mujoco.py --env-id Hopper-v4 --n-clusters 6 --truncate-step 1000 --seed 1

# for SnapshotRL+STT+TD3
python src/snapshot_td3_mujoco_random.py --env-id Hopper-v4 --truncate-step 100 --seed 1

# for SnapshotRL+TD3
python src/snapshot_td3_mujoco_random.py --env-id Hopper-v4 --truncate-step 1000 --seed 1


# for S3RL+SAC
python src/snapshot_sac_mujoco.py --env-id Hopper-v4 --n-clusters 6 --truncate-step 100 --seed 1

# for S3RL+PPO
python src/snapshot_ppo_fix_mujoco.py --env-id Hopper-v4 --n-clusters 6 --truncate-step 100 --seed 1

Citing this work

@article{zhao2024snapshot,
  title={Snapshot Reinforcement Learning: Leveraging Prior Trajectories for Efficiency},
  author={Zhao, Yanxiao and Qian, Yangge and Wang, Tianyi and Shan, Jingyang and Qin, Xiaolin},
  journal={arXiv preprint arXiv:2403.00673},
  year={2024}
}