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Online Pre-Training for Offline-to-Online RL

This repository contains the official implementation of Online Pre-Training for Offline-to-Online RL (OPT).

Installation

OPT is implemented in Python 3.9 and built using PyTorch. To install the required dependencies, run:

pip install -r requriements.txt

Getting Started

The core implementation of OPT can be found in algorithms/opt.py, and the IQL + OPT variant is available in algorithms/iql_opt.py Example commands:

python algorithms/opt.py --config_path=configs/opt/walker2d/random_v2.yaml
python algorithms/opt.py --config_path=configs/opt/antmaze/umaze_v2.yaml

Acknowledgments

This codebase builds upon the implementation from CORL.

Contact

If you have any questions or inquiries, please feel free to contact us at:
yongjae.shin@kaist.ac.kr, kanghoon.lee@lgresearch.ai

About

Official implementation of "Online Pre-Training for Offline-to-Online Reinforcement Learning" (ICML 2025) by LG AI Research.

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