Flexible Option Learning - NeurIPS 2021

Related tags

Deep LearningMOC
Overview

Flexible Option Learning

This repository contains code for the paper Flexible Option Learning presented as a Spotlight at NeurIPS 2021. The implementation is based on gym-miniworld, OpenAI's baselines and the Option-Critic's tabular implementation.

Contents:

Tabular Experiments (Four-Rooms)

Installation and Launch code

pip install gym==0.12.1
cd diagnostic_experiments/
python main_fixpol.py --multi_option # for experiments with fixed options
python main.py --multi_option # for experiments with learned options

Continuous Control (MuJoCo)

Installation

virtualenv moc_cc --python=python3
source moc_cc/bin/activate
pip install tensorflow==1.12.0 
cd continuous_control
pip install -e . 
pip install gym==0.9.3
pip install mujoco-py==0.5.1

Launch

cd baselines/ppoc_int
python run_mujoco.py --switch --nointfc --env AntWalls --eta 0.9 --mainlr 8e-5 --intlr 8e-5 --piolr 8e-5

Maze Navigation (MiniWorld)

Installation

virtualenv moc_vision --python=python3
source moc_vision/bin/activate
pip install tensorflow==1.13.1
cd vision_miniworld
pip install -e .
pip install gym==0.15.4

Launch

cd baselines/
# Run agent in first task
python run.py --alg=ppo2_options --env=MiniWorld-WallGap-v0 --num_timesteps 2500000 --save_interval 1000  --num_env 8 --noptions 4 --eta 0.7

# Load and run agent in transfer task
python run.py --alg=ppo2_options --env=MiniWorld-WallGapTransfer-v0 --load_path path/to/model --num_timesteps 2500000 --save_interval 1000  --num_env 8 --noptions 4 --eta 0.7

Cite

If you find this work useful to you, please consider adding you to your references.

@inproceedings{
klissarov2021flexible,
title={Flexible Option Learning},
author={Martin Klissarov and Doina Precup},
booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
year={2021},
url={https://openreview.net/forum?id=L5vbEVIePyb}
}
Owner
Martin Klissarov
PhD student at McGill University
Martin Klissarov
Deep Learning for Morphological Profiling

Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di

Danielh Carranza 0 Jan 20, 2022
For visualizing the dair-v2x-i dataset

3D Detection & Tracking Viewer The project is based on hailanyi/3D-Detection-Tracking-Viewer and is modified, you can find the original version of the

34 Dec 29, 2022
[ICML 2021] Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data

Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised

Michihiro Yasunaga 86 Nov 30, 2022
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

Ruotian(RT) Luo 906 Jan 03, 2023
Ladder Variational Autoencoders (LVAE) in PyTorch

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

Andrea Dittadi 63 Dec 22, 2022
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022

Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema

Pgxo20 24 Jan 02, 2023
Website for D2C paper

D2C This is the repository that contains source code for the D2C Website. If you find D2C useful for your work please cite: @article{sinha2021d2c au

1 Oct 21, 2021
ICRA 2021 "Towards Precise and Efficient Image Guided Depth Completion"

PENet: Precise and Efficient Depth Completion This repo is the PyTorch implementation of our paper to appear in ICRA2021 on "Towards Precise and Effic

232 Dec 25, 2022
Migration of Edge-based Distributed Federated Learning

FedFly: Towards Migration in Edge-based Distributed Federated Learning About the research Due to mobility, a device participating in Federated Learnin

qub-blesson 11 Nov 13, 2022
The official implementation of CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing

CSGStumpNet The official implementation of CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing Paper | Project page

Daxuan 39 Dec 26, 2022
Embodied Intelligence via Learning and Evolution

Embodied Intelligence via Learning and Evolution This is the code for the paper Embodied Intelligence via Learning and Evolution Agrim Gupta, Silvio S

Agrim Gupta 111 Dec 13, 2022
The Python3 import playground

The Python3 import playground I have been confused about python modules and packages, this text tries to clear the topic up a bit. Sources: https://ch

Michael Moser 5 Feb 22, 2022
DIRL: Domain-Invariant Representation Learning

DIRL: Domain-Invariant Representation Learning Domain-Invariant Representation Learning (DIRL) is a novel algorithm that semantically aligns both the

Ajay Tanwani 30 Nov 07, 2022
Our CIKM21 Paper "Incorporating Query Reformulating Behavior into Web Search Evaluation"

Reformulation-Aware-Metrics Introduction This codebase contains source-code of the Python-based implementation of our CIKM 2021 paper. Chen, Jia, et a

xuanyuan14 5 Mar 05, 2022
The pure and clear PyTorch Distributed Training Framework.

The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base

WILL LEE 208 Dec 20, 2022
Bridging Vision and Language Model

BriVL BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果,超过了同期其他常见的多模态预训练模型(例如UNITER、CLIP)。 BriVL论文:WenLan: Bridgi

235 Dec 27, 2022
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation

Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation [Arxiv] [Video] Evaluation code for Unrestricted Facial Geometry Reconstr

Matan Sela 242 Dec 30, 2022
Training RNNs as Fast as CNNs

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

ASAPP Research 2.1k Jan 01, 2023
Fully Convolutional DenseNets for semantic segmentation.

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

485 Nov 26, 2022
Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"

NeuralSymbolicRegressionThatScales Pytorch implementation and pretrained models for the paper "Neural Symbolic Regression That Scales", presented at I

35 Nov 25, 2022