High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
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Updated
Aug 3, 2023 - Python
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
A Japanese (Riichi) Mahjong AI Framework
An elegant PyTorch offline reinforcement learning library for researchers.
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
A collection of offline reinforcement learning algorithms.
Datasets with baselines for offline multi-agent reinforcement learning.
PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.
Python interface for accessing the near real-world offline reinforcement learning (NeoRL) benchmark datasets
Clean single-file implementation of offline RL algorithms in JAX
Code release for Efficient Planning in a Compact Latent Action Space (ICLR2023) https://arxiv.org/abs/2208.10291.
[ICLR 2024] The official implementation of "Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model"
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
Pytorch Implementation of Stochastic MuZero for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
[NeurIPS 2022 Oral] The official implementation of POR in "A Policy-Guided Imitation Approach for Offline Reinforcement Learning"
Author's implementation of ReBRAC, a minimalist improvement upon TD3+BC
Official implementation for "Anti-Exploration by Random Network Distillation", ICML 2023
Code for FOCAL Paper Published at ICLR 2021
Single-file SAC-N implementation on jax with flax and equinox. 10x faster than pytorch
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