OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

An offline deep reinforcement learning library

An index of algorithms for offline reinforcement learning (offline-rl)

Summary of key papers and blogs about diffusion models to learn about the topic. Detailed list of all published diffusion robotics papers.

Related papers for reinforcement learning, including classic papers and latest papers in top conferences

A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities

DI-engine docs (Chinese and English)

A Japanese (Riichi) Mahjong AI Framework

Official code from the paper "Offline RL for Natural Language Generation with Implicit Language Q Learning"

🤖 Elegant implementations of offline safe RL algorithms in PyTorch

A large-scale multi-modal pre-trained model

SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection

ExORL: Exploratory Data for Offline Reinforcement Learning

An out-of-the-box GUI tool for offline deep reinforcement learning

Clean single-file implementation of offline RL algorithms in JAX

Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).

Extreme Q-Learning: Max Entropy RL without Entropy

official implementation for our paper Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

🔥 Datasets and env wrappers for offline safe reinforcement learning

Benchmarked implementations of Offline RL Algorithms.