RL-GAN: Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

Related tags

Deep LearningRL-GAN
Overview

RL-GAN: Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

RL-GAN is an official implementation of the paper: Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation.

Paper

Shani Gamrian, Yoav Goldberg, "Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation"

@article{DBLP:journals/corr/abs-1806-07377,
  author    = {Shani Gamrian and
               Yoav Goldberg},
  title     = {Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image
               Translation},
  journal   = {CoRR},
  volume    = {abs/1806.07377},
  year      = {2018},
  url       = {http://arxiv.org/abs/1806.07377},
  archivePrefix = {arXiv},
  eprint    = {1806.07377},
  timestamp = {Mon, 13 Aug 2018 16:48:23 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1806-07377},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Videos:

Breakout

RoadFighter

Installation

  • The code was tested on Ubuntu 16.04 with Python 3.6
  • Install packages by typing the command: pip install -r requirements.txt.
  • For Road Fighter, clone and install the repo: https://github.com/ShaniGam/retro

Getting Started

Breakout Examples

  • Train Breakout from scratch:
python -m breakout_a3c.main --num-processes 32 --variation 'standart'
  • Transfer from standart to diagonals variation and fine-tune the model:
python -m breakout_a3c.main --num-processes 32 --variation diagonals --ft-setting full-ft --test
  • Collect images for UNIT training:
python -m breakout_a3c.main --collect-images --num-collected-imgs 100000 --variation diagonals --num-processes 1
  • Train UNIT:
python -m unit.train --trainer UNIT --config unit/configs/breakout-diagonals.yaml
  • Run Breakout with UNIT:
python -m breakout_a3c.main --variation diagonals --test --ft-setting full-ft --test-gan --gan-dir breakout-diagonals --num-processes 0

Road Fighter Examples

  • Train level 1 of Road Fighter
python -m roadfighter_a2c.main --num-processes 84
  • Collect images for UNIT training:
python -m roadfighter_a2c.main -level 1 --collect-images --num-collected-imgs 100000 --num-processes 1
python -m roadfighter_a2c.main -level 2 --collect-images --num-collected-imgs 100000 --num-processes 1
  • Train UNIT:
python -m unit.train --trainer UNIT --config unit/configs/roadfighter-lvl2.yaml
  • Run Road Fighter with UNIT:
python -m roadfighter_a2c.main --load --level 2 --test-gan --gan-dir roadfighter-lvl2-kl01 --num-processes 1
  • Run Road Fighter with UNIT and Imitation Learning:
python -m roadfighter_a2c.main_imitation --load --gan-dir roadfighter-lvl2-kl01 --gan-imitation-file '00320000' --log-name lvl2.log --super-during-rl --level 2 --det-score 5350

Acknowledgments

The code was written by Shani Gamrian and is based on the repositories: pytorch-a3c, pytorch-a2c, UNIT

TO-DO

  • Add links for pretrained models.
  • Create videos.
The official TensorFlow implementation of the paper Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition

Action Transformer A Self-Attention Model for Short-Time Human Action Recognition This repository contains the official TensorFlow implementation of t

PIC4SeRCentre 20 Jan 03, 2023
R-Drop: Regularized Dropout for Neural Networks

R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi

756 Dec 27, 2022
A multi-scale unsupervised learning for deformable image registration

A multi-scale unsupervised learning for deformable image registration Shuwei Shao, Zhongcai Pei, Weihai Chen, Wentao Zhu, Xingming Wu and Baochang Zha

ShuweiShao 2 Apr 13, 2022
Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available for research purposes.

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available f

Yongrui Chen 5 Nov 10, 2022
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans

Abhay Gupta 161 Dec 08, 2022
Ganilla - Official Pytorch implementation of GANILLA

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

Samet Hi 462 Dec 05, 2022
Neon-erc20-example - Example of creating SPL token and wrapping it with ERC20 interface in Neon EVM

Example of wrapping SPL token by ERC2-20 interface in Neon Requirements Install

7 Mar 28, 2022
The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"

The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"

Ren Yurui 261 Jan 09, 2023
An Implementation of Fully Convolutional Networks in Tensorflow.

Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo

Marvin Teichmann 1.1k Dec 12, 2022
Deep ViT Features as Dense Visual Descriptors

dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe

Shir Amir 113 Dec 24, 2022
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory

Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate

2 Mar 02, 2022
A Python library for common tasks on 3D point clouds

Point Cloud Utils (pcu) - A Python library for common tasks on 3D point clouds Point Cloud Utils (pcu) is a utility library providing the following fu

Francis Williams 622 Dec 27, 2022
A curated list of awesome game datasets, and tools to artificial intelligence in games

🎮 Awesome Game Datasets In computer science, Artificial Intelligence (AI) is intelligence demonstrated by machines. Its definition, AI research as th

Leonardo Mauro 454 Jan 03, 2023
A Python package for causal inference using Synthetic Controls

Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim

Oscar Engelbrektson 107 Dec 28, 2022
Implementation of ConvMixer for "Patches Are All You Need? 🤷"

Patches Are All You Need? 🤷 This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?" by Asher

CMU Locus Lab 934 Jan 08, 2023
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)

This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the offi

789 Jan 04, 2023
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce (EMNLP Founding 2021)

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Xu Song 21 Nov 16, 2022
Background-Click Supervision for Temporal Action Localization

Background-Click Supervision for Temporal Action Localization This repository is the official implementation of BackTAL. In this work, we study the te

LeYang 221 Oct 09, 2022
GUPNet - Geometry Uncertainty Projection Network for Monocular 3D Object Detection

GUPNet This is the official implementation of "Geometry Uncertainty Projection Network for Monocular 3D Object Detection". citation If you find our wo

Yan Lu 103 Dec 28, 2022