OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
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Updated
Jul 19, 2024 - Python
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
An offline deep reinforcement learning library
DI-engine docs (Chinese and English)
A Japanese (Riichi) Mahjong AI Framework
A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities
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
Extreme Q-Learning: Max Entropy RL without Entropy
Clean single-file implementation of offline RL algorithms in JAX
Benchmarked implementations of Offline RL Algorithms.
🔥 Datasets and env wrappers for offline safe reinforcement learning
PyTorch implementation of the implicit Q-learning algorithm (IQL)
Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).
Model-based Offline Policy Optimization re-implement all by pytorch
Codes for "Efficient Offline Policy Optimization with a Learned Model", ICLR2023
code for paper Query-Dependent Prompt Evaluation and Optimization with Offline Inverse Reinforcement Learning
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