An offline deep reinforcement learning library
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Updated
Jul 7, 2024 - Python
An offline deep reinforcement learning library
Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).
OpenDILab Decision AI Engine
DI-engine docs (Chinese and English)
PyTorch Implementation of MOPO
A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities
Clean single-file implementation of offline RL algorithms in JAX
Implemenation of CORL for Fetch and Unitree A1 tasks
Summarising the research of Offline RL in Federated Setting.
A Japanese (Riichi) Mahjong AI Framework
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
Reinforcement Learning Short Course
An index of algorithms for offline reinforcement learning (offline-rl)
Benchmarked implementations of Offline RL Algorithms.
code for paper Query-Dependent Prompt Evaluation and Optimization with Offline Inverse Reinforcement Learning
🧠 Learning World Value Functions without Exploration
SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection
Need 4 Speed, FYP 2023-24 @ Monash.
Author's repository for GSM8K-AI-SubQ reasoning dataset
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