Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)

Related tags

Deep Learningoffline-reinforcement-learning
Overview

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

DOI License: MIT

This is the code for reproducing the results of the paper Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble accepted at NeurIPS'2021.

This code builds up from the offical code of Reset-Free Lifelong Learning with Skill-Space Planning, originally derived from rlkit.

If you find this repository useful for your research, please cite:

@inproceedings{
    an2021edac,
    title={Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble},
    author={Gaon An and Seungyong Moon and Jang-Hyun Kim and Hyun Oh Song},
    booktitle={Neural Information Processing Systems},
    year={2021}
}

Requirements

To install all the required dependencies:

  1. Install MuJoCo engine, which can be downloaded from here.

  2. Install Python packages listed in requirements.txt using pip. You should specify the versions of mujoco_py and dm_control in requirements.txt depending on the version of MuJoCo engine you have installed as follows:

    • MuJoCo 2.0: mujoco-py<2.1,>=2.0, dm_control==0.0.364896371
    • MuJoCo 2.1.0: mujoco-py<2.2,>=2.1, dm_control==0.0.403778684
    • MuJoCo 2.1.1: to be updated

  3. Manually download and install d4rl package from here. You should remove lines including dm_control in setup.py.

Here is an example of how to install all the dependencies on Ubuntu:

conda create -n edac python=3.7
conda activate edac
# Specify versions of mujoco-py and dm_control in requirements.txt
pip install --no-cache-dir -r requirements.txt

cd .
git clone https://github.com/rail-berkeley/d4rl.git

cd d4rl
# Remove lines including 'dm_control' in setup.py
pip install -e .

Reproducing the results

Gym

To reproduce SAC-N results for MuJoCo Gym, run:

python -m scripts.sac --env_name [ENVIRONMENT] --num_qs [N]

To reproduce EDAC results for MuJoCo Gym, run:

python -m scripts.sac --env_name [ENVIRONMENT] --num_qs [N] --eta [ETA]

Adroit

On Adroit tasks, we apply reward normalization for further training stability. For example, to reproduce the EDAC results for pen-human, run:

python -m scripts.sac --env_name pen-human-v1 --epoch 200 --num_qs 20 --plr 3e-5 --eta 1000 --reward_mean --reward_std

To reproduce the EDAC results for pen-cloned, run:

python -m scripts.sac --env_name pen-human-v1 --epoch 200 --num_qs 20 --plr 3e-5 --eta 10 --max_q_backup --reward_mean --reward_std

Acknowledgement

This work was supported in part by Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd., Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2020-0-00882, (SW STAR LAB) Development of deployable learning intelligence via self-sustainable and trustworthy machine learning and No. 2019-0-01371, Development of brain-inspired AI with human-like intelligence), and Research Resettlement Fund for the new faculty of Seoul National University. This material is based upon work supported by the Air Force Office of Scientific Research under award number FA2386-20-1-4043.

You might also like...
Official PyTorch implementation of Spatial Dependency Networks.
Official PyTorch implementation of Spatial Dependency Networks.

Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling Đorđe Miladinović   Aleksandar Stanić   Stefan Bauer   Jürgen Schmid

Djordje Miladinovic 34 Jan 19, 2022
Official implementation of our CVPR2021 paper
Official implementation of our CVPR2021 paper "OTA: Optimal Transport Assignment for Object Detection" in Pytorch.

OTA: Optimal Transport Assignment for Object Detection This project provides an implementation for our CVPR2021 paper "OTA: Optimal Transport Assignme

null 217 Jan 3, 2023
This is the official PyTorch implementation of the paper
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

Ju He 307 Jan 3, 2023
StyleGAN2-ADA - Official PyTorch implementation
StyleGAN2-ADA - Official PyTorch implementation

Need Help? If you’re new to StyleGAN2-ADA and looking to get started, please check out this video series from a course Lia Coleman and I taught in Oct

Derrick Schultz 217 Jan 4, 2023
Official PyTorch implementation of
Official PyTorch implementation of "ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows"

ArtFlow Official PyTorch implementation of the paper: ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows Jie An*, Siyu Huang*, Yibing

null 123 Dec 27, 2022
Official PyTorch implementation of RobustNet (CVPR 2021 Oral)
Official PyTorch implementation of RobustNet (CVPR 2021 Oral)

RobustNet (CVPR 2021 Oral): Official Project Webpage Codes and pretrained models will be released soon. This repository provides the official PyTorch

Sungha Choi 173 Dec 21, 2022
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic

Hila Chefer 489 Jan 7, 2023
[PyTorch] Official implementation of CVPR2021 paper
[PyTorch] Official implementation of CVPR2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency". https://arxiv.org/abs/2103.05465

PointDSC repository PyTorch implementation of PointDSC for CVPR'2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency",

null 153 Dec 14, 2022
Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

Clova AI Research 97 Dec 23, 2022
Comments
  • Performance on D4RL AntMaze tasks?

    Performance on D4RL AntMaze tasks?

    Hello, I have a question about the performance of SAC-N or EDAC on AntMaze tasks. Have you ever tested it?

    In my experiments based on this official implementation, I found that average returns in evaluation are always 0, which is worse than behavior cloning. Then I try to run with a modified reward (r=4*(r-0.5)) and max Q backup. However, they didn't help.

    I'll appreciate it a lot if you give me some related advices. Thanks a lot.

    opened by yuxudong20 3
Releases(v1.0)
Owner
GitHub Repository
code for our BMVC 2021 paper "HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification"

HCV_IIRC code for our BMVC 2021 paper HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification by Kai Wang, Xialei Li

kai wang 13 Oct 03, 2022
Toward Spatially Unbiased Generative Models (ICCV 2021)

Toward Spatially Unbiased Generative Models Implementation of Toward Spatially Unbiased Generative Models (ICCV 2021) Overview Recent image generation

Jooyoung Choi 88 Dec 01, 2022
This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

551 Dec 29, 2022
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.

RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very

Vishal R 2 Feb 11, 2022
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

Jonathan Choi 2 Mar 17, 2022
Implementation of Feedback Transformer in Pytorch

Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce

Phil Wang 93 Oct 04, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

152 Jan 02, 2023
Lua-parser-lark - An out-of-box Lua parser written in Lark

An out-of-box Lua parser written in Lark Such parser handles a relaxed version o

Taine Zhao 2 Jul 19, 2022
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation [arxiv] This is the official repository for CDTrans: Cross-domain Transformer for

238 Dec 22, 2022
Using VideoBERT to tackle video prediction

VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/M

75 Dec 14, 2022
Cross-media Structured Common Space for Multimedia Event Extraction (ACL2020)

Cross-media Structured Common Space for Multimedia Event Extraction Table of Contents Overview Requirements Data Quickstart Citation Overview The code

Manling Li 49 Nov 21, 2022
HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR. CVPR 2022

HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR. CVPR 2022 [Project page | Video] Getting sta

51 Nov 29, 2022
A spherical CNN for weather forecasting

DeepSphere-Weather - Deep Learning on the sphere for weather/climate applications. The code in this repository provides a scalable and flexible framew

DeepSphere 47 Dec 25, 2022
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Google Research 258 Dec 29, 2022
[PAMI 2020] Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation

Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation This repository contains the source code for

Yun-Chun Chen 60 Nov 25, 2022
The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".

Code for "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval" (ACL 2021, Long) This is the repository for baseline m

Akari Asai 25 Oct 30, 2022
Implementation of SwinTransformerV2 in TensorFlow.

SwinTransformerV2-TensorFlow A TensorFlow implementation of SwinTransformerV2 by Microsoft Research Asia, based on their official implementation of Sw

Phan Nguyen 2 May 30, 2022
Supervised Classification from Text (P)

MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from

Matthew Laws 1 Nov 22, 2021
CIFAR-10 Photo Classification

Image-Classification CIFAR-10 Photo Classification CIFAR-10_Dataset_Classfication CIFAR-10 Photo Classification Dataset CIFAR is an acronym that stand

ADITYA SHAH 1 Jan 05, 2022
A study project using the AA-RMVSNet to reconstruct buildings from multiple images

3d-building-reconstruction This is part of a study project using the AA-RMVSNet to reconstruct buildings from multiple images. Introduction It is exci

17 Oct 17, 2022