Implementation of Change-Based Exploration Transfer (C-BET)

Related tags

Deep Learningreinforcement-learningexploration
Overview

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Implementation of Change-Based Exploration Transfer (C-BET), as presented in Interesting Object, Curious Agent: Learning Task-Agnostic Exploration.

This code was built on the RIDE repository.

Codebase and MiniGrid Installation

conda create -n cbet python=3.8.10
conda activate cbet
git clone [email protected]:sparisi/cbet.git
cd cbet
pip install -r requirements.txt

Habitat Installation (not Needed for MiniGrid Experiments)

  • Follow the official guide and do a full install with habitat_baselines.
  • Download and extract Replica scenes in the root folder of cbet

WARNING! The dataset is very large!

sudo apt-get install pigz
git clone https://github.com/facebookresearch/Replica-Dataset.git
cd Replica-Dataset
./download.sh replica-path

If the script does not work, manually unzip with cat replica_v1_0.tar.gz.part* | tar -xz

How to Run Experiments

  • Intrinsic-only pre-training: OMP_NUM_THREADS=1 python main.py --model cbet --env --no_reward --intrinsic_reward_coef=0.005

  • Extrinsic-only transfer with pre-trained model: OMP_NUM_THREADS=1 python main.py --model cbet --env --intrinsic_reward_coef=0.0 --checkpoint=path/to/model.tar

  • Tabula-rasa training with summed intrinsic and extrinsic reward: OMP_NUM_THREADS=1 python main.py --model cbet --env --intrinsic_reward_coef=0.005

See src/arguments.py for the full list of hyperparameters.

For MiniGrid, can be MiniGrid-DoorKey-8x8-v0, MiniGrid-Unlock-v0, ...
For Habitat, can be HabitatNav-apartment_0, HabitatNav-hotel_0, ...

You might also like...
RE3: State Entropy Maximization with Random Encoders for Efficient Exploration

State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f

Younggyo Seo 47 Nov 29, 2022
Generative Exploration and Exploitation - This is an improved version of GENE.
Generative Exploration and Exploitation - This is an improved version of GENE.

GENE This is an improved version of GENE. In the original version, the states are generated from the decoder of VAE. We have to check whether the gere

null 33 Mar 23, 2022
Systemic Evolutionary Chemical Space Exploration for Drug Discovery
Systemic Evolutionary Chemical Space Exploration for Drug Discovery

SECSE SECSE: Systemic Evolutionary Chemical Space Explorer Chemical space exploration is a major task of the hit-finding process during the pursuit of

null 64 Dec 16, 2022
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ↔ transc

Phil Wang 62 Dec 20, 2022
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code

Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code

STARS Laboratory 8 Sep 14, 2022
Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment
Multi-robot collaborative exploration and mapping through Voronoi partition and DRL in unknown environment

Voronoi Multi_Robot Collaborate Exploration Introduction In the unknown environment, the cooperative exploration of multiple robots is completed by Vo

PeaceWord 6 Nov 22, 2022
[TIP 2020] Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion
[TIP 2020] Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion

Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion Code for Multi-Temporal Scene Classification and Scene Ch

Lixiang Ru 33 Dec 12, 2022
Remote sensing change detection tool based on PaddlePaddle

PdRSCD PdRSCD（PaddlePaddle Remote Sensing Change Detection）是一个基于飞桨PaddlePaddle的遥感变化检测的项目，pypi包名为ppcd。目前0.2版本，最新支持图像列表输入的训练和预测，如多期影像、多源影像甚至多期多源影像。可以快速完

null 38 Aug 31, 2022
TransCD: Scene Change Detection via Transformer-based Architecture
TransCD: Scene Change Detection via Transformer-based Architecture

TransCD: Scene Change Detection via Transformer-based Architecture

wangzhixue 29 Dec 11, 2022
Comments
  • Bugfixes

    Bugfixes

    • Fixed a crash with Habitat environment in test script due to missing directory
    • Fixed an issue where count_reset_prob is referenced, but is not tracked in the ArgumentParser by removing it
    • Worked around a PyTorch memory bug (Ubuntu 21.10 + Driver Version: 495.29.05 + CUDA Version: 11.5 + torch version: 1.10.1+cu113)
      • Failed to allocate SHM despite plenty of available handles and many GiB of both system and GPU memory
      • Error message indicated an internal PyTorch bug, with instructions for filing a ticket
    opened by rothn 0
  • Problem about intrinsic reward at pre-training stage

    Problem about intrinsic reward at pre-training stage

    Hi,

    I think I meet a problem that my results of intrinsic reward is about 0.0014 after training of 4e7 frames and I just follow the instruction of github without changing any parameters, the environments I use is MiniGrid-KeyCorridorS3R3-v0,MiniGrid-MultiRoom-N4-S5-v0,MiniGrid-UnlockPickup-v0, which are mentioned in the paper as pre-training of many-to-many transfer. Therefore, I don't know whether there are something I missed. Hoping you can help me. Thx a lot.

    opened by dong845 2
  • Pretrained Model

    Pretrained Model

    One of my favorite components of the C-BET paper was the proposed paradigm shift from tabula-rasa exploration for each task to a system where new environments are explored with the context carried over from a pretrained model. I've found that a practical starting point for similar procedures on other large models (e.g., BERTs, ResNets) is to obtain a copy of the pre-trained model. I'd love to start working with C-BET as well!

    I'm very curious as to where I might be able to find the C-BET parameters from your paper. Looking forward to experimenting with this!

    opened by rothn 9
Releases(v1)
Owner
Simone Parisi
Simone Parisi
GitHub Repository
Attention for PyTorch with Linear Memory Footprint

Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+

11 Jan 09, 2022
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Thuy Ng 474 Dec 19, 2022
StarGAN - Official PyTorch Implementation (CVPR 2018)

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Yunjey Choi 5.1k Dec 30, 2022
Explanatory Learning: Beyond Empiricism in Neural Networks

Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets

GLADIA Research Group 10 Dec 06, 2022
Council-GAN - Implementation for our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020)

Council-GAN Implementation of our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020) Paper Ori Nizan , Ayellet Tal, Breaking the Cycle

ori nizan 260 Nov 16, 2022
Multi-scale discriminator feature-wise loss function

Multi-Scale Discriminative Feature Loss This repository provides code for Multi-Scale Discriminative Feature (MDF) loss for image reconstruction algor

Graphics and Displays group - University of Cambridge 76 Dec 12, 2022
MultiLexNorm 2021 competition system from ÚFAL

ÚFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5 David Samuel & Milan Straka Charles University Faculty of

ÚFAL 13 Jun 28, 2022
NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation (ACL-IJCNLP 2021)

NeuralWOZ This code is official implementation of "NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation". Sungdong Kim, Mi

NAVER AI 31 Oct 25, 2022
This is the official github repository of the Met dataset

The Met dataset This is the official github repository of the Met dataset. The official webpage of the dataset can be found here. What is it? This cod

Nikolaos-Antonios Ypsilantis 35 Dec 17, 2022
[EMNLP 2021] MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

MuVER This repo contains the code and pre-trained model for our EMNLP 2021 paper: MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity

24 May 30, 2022
Code for the paper "Graph Attention Tracking". (CVPR2021)

SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r

122 Dec 24, 2022
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.

signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled

Will Glad 1 Mar 11, 2022
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase

Ranger-Deep-Learning-Optimizer Ranger - a synergistic optimizer combining RAdam (Rectified Adam) and LookAhead, and now GC (gradient centralization) i

Less Wright 1.1k Dec 21, 2022
A whale detector design for the Kaggle whale-detector challenge!

CNN (InceptionV1) + STFT based Whale Detection Algorithm So, this repository is my PyTorch solution for the Kaggle whale-detection challenge. The obje

Tarin Ziyaee 92 Sep 28, 2021
Construct a neural network frame by Numpy

本项目的CSDN博客链接：https://blog.csdn.net/weixin_41578567/article/details/111482022 1. 概览 本项目主要用于神经网络的学习，通过基于numpy的实现，了解神经网络底层前向传播、反向传播以及各类优化器的原理。 该项目目前已实现的功

24 Jan 22, 2022
SmoothGrad implementation in PyTorch

SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro

SSKH 143 Jan 05, 2023
Official code of our work, AVATAR: A Parallel Corpus for Java-Python Program Translation.

AVATAR Official code of our work, AVATAR: A Parallel Corpus for Java-Python Program Translation. AVATAR stands for jAVA-pyThon progrAm tRanslation. AV

Wasi Ahmad 26 Dec 03, 2022
Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image

Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image This repository is an implementation of the method described in the following pap

21 Dec 15, 2022
A library for using chemistry in your applications

Chemistry in python Resources Used The following items are not made by me! Click the words to go to the original source Periodic Tab Json - Used in -

Tech Penguin 28 Dec 17, 2021
Y. Zhang, Q. Yao, W. Dai, L. Chen. AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. IEEE International Conference on Data Engineering (ICDE). 2020

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

AutoML Research 64 Dec 17, 2022