Offline Reinforcement Learning with Implicit Q-Learning

This repository contains the official implementation of Offline Reinforcement Learning with Implicit Q-Learning by Ilya Kostrikov, Ashvin Nair, and Sergey Levine.

If you use this code for your research, please consider citing the paper:

@article{kostrikov2021iql,
    title={Offline Reinforcement Learning with Implicit Q-Learning},
    author={Ilya Kostrikov and Ashvin Nair and Sergey Levine},
    year={2021},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

How to run the code

Install dependencies

pip install -r requirements.txt

See instructions for CUDA.

Run training

Locomotion

python train_offline.py --env_name=halfcheetah-medium-expert-v2 --config=configs/mujoco_config.py

AntMaze

python train_offline.py --env_name=antmaze-large-play-v0 --config=configs/antmaze_config.py --eval_episodes=100 --eval_interval=100000

Kitchen and Adroit

python train_offline.py --env_name=pen-human-v0 --config=configs/kitchen_config.py

Misc

The implementation is based on JAXRL.

Offline Reinforcement Learning with Implicit Q-Learning

Related tags

Overview

Offline Reinforcement Learning with Implicit Q-Learning

How to run the code

Install dependencies

Run training

Misc

Owner

Ilya Kostrikov

Generic image compressor for machine learning. Pytorch code for our paper "Lossy compression for lossless prediction".

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

Official code for CVPR2022 paper: Depth-Aware Generative Adversarial Network for Talking Head Video Generation

This is the official Pytorch implementation of the paper "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"

This repo includes the CUB-GHA (Gaze-based Human Attention) dataset and code of the paper "Human Attention in Fine-grained Classification".

atmaCup #11 の Public 4th / Pricvate 5th Solution のリポジトリです。

Reinforcement Learning for the Blackjack

Implementation for the IJCAI2021 work "Beyond the Spectrum: Detecting Deepfakes via Re-synthesis"

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)

Machine learning notebooks in different subjects optimized to run in google collaboratory

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️

A modular application for performing anomaly detection in networks

Node-level Graph Regression with Deep Gaussian Process Models

FFCV: Fast Forward Computer Vision (and other ML workloads!)

Dynamical Wasserstein Barycenters for Time Series Modeling

minimizer-space de Bruijn graphs (mdBG) for whole genome assembly

Landmarks Recogntion Web application using Streamlit.

Long Expressive Memory (LEM)