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Wei Xiao's Projects

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bcq icon bcq

Author's PyTorch implementation of BCQ for continuous and discrete actions

bear icon bear

Code for Stabilizing Off-Policy RL via Bootstrapping Error Reduction

cped icon cped

The code implementation of paper "Constrained Policy Optimization with Explicit Behavior Density for Offline Reinforcement Learning"

howtocook icon howtocook

程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).

iql-pytorch icon iql-pytorch

Unofficial PyTorch implementation (replicating paper results) of Implicit Q-Learning (In-sample Q-Learning) for offline RL

ivr icon ivr

[ICLR 2023 Oral] The official implementation of SQL and EQL in "Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization"

linux-command icon linux-command

Linux命令大全搜索工具,内容包含Linux命令手册、详解、学习、搜集。https://git.io/linux

mcq icon mcq

Code for Mildly Conservative Q-learning for Offline Reinforcement Learning (NeurIPS 2022)

oema icon oema

Official PyTorch code for "Sample Efficient Offline-to-Online Reinforcement Learning" in TKDE'23.

prdc icon prdc

Author's PyTorch implementation of ICML'23 paper "Policy Regularization with Dataset Constraint for Offline Reinforcement Learning" for D4RL gym and AntMaze tasks.

sac icon sac

PyTorch implementation of Soft Actor-Critic (SAC)

sbac icon sbac

Facebear's minimal implementation of SBAC (Soft behavior regularized actor critic, NIPS22 offline RL workshop)

spot icon spot

Code release for "Supported Policy Optimization for Offline Reinforcement Learning" (NeurIPS 2022), https://arxiv.org/abs/2202.06239

svr icon svr

Code for Supported Value Regularization for Offline Reinforcement Learning

td3 icon td3

Author's PyTorch implementation of TD3 for OpenAI gym tasks

td3_bc icon td3_bc

Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

wpc icon wpc

Implementation for " weighted policy constraints for offline reinforcement learning"

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