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
Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende

Machine Learning and Computational Biology Lab 16 Oct 16, 2022
Computer Vision application in the web

Computer Vision application in the web Preview Usage Clone this repo git clone https://github.com/amineHY/WebApp-Computer-Vision-streamlit.git cd Web

Amine Hadj-Youcef. PhD 35 Dec 06, 2022
Romanian Automatic Speech Recognition from the ROBIN project

RobinASR This repository contains Robin's Automatic Speech Recognition (RobinASR) for the Romanian language based on the DeepSpeech2 architecture, tog

RACAI 10 Jan 01, 2023
Shuffle Attention for MobileNetV3

SA-MobileNetV3 Shuffle Attention for MobileNetV3 Train Run the following command for train model on your own dataset: python train.py --dataset mnist

Sajjad Aemmi 36 Dec 28, 2022
Just-Now - This Is Just Now Login Friendlist Cloner Tools

JUST NOW LOGIN FRIENDLIST CLONER TOOLS Install $ apt update $ apt upgrade $ apt

MAHADI HASAN AFRIDI 21 Mar 09, 2022
UPSNet: A Unified Panoptic Segmentation Network

UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te

Uber Research 622 Dec 26, 2022
OMNIVORE is a single vision model for many different visual modalities

Omnivore: A Single Model for Many Visual Modalities [paper][website] OMNIVORE is a single vision model for many different visual modalities. It learns

Meta Research 451 Dec 27, 2022
Convolutional Neural Network for Text Classification in Tensorflow

This code belongs to the "Implementing a CNN for Text Classification in Tensorflow" blog post. It is slightly simplified implementation of Kim's Convo

Denny Britz 5.5k Jan 02, 2023
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env

48 Dec 20, 2022
Zero-shot Learning by Generating Task-specific Adapters

Code for "Zero-shot Learning by Generating Task-specific Adapters" This is the repository containing code for "Zero-shot Learning by Generating Task-s

INK Lab @ USC 11 Dec 17, 2021
This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild with Dense 3D Representations and A Benchmark. (CVPR 2022)"

Gait3D-Benchmark This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild

82 Jan 04, 2023
traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation toolbox based on PyTorch.

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

202 Jan 04, 2023
Object tracking using YOLO and a tracker(KCF, MOSSE, CSRT) in openCV

Object tracking using YOLO and a tracker(KCF, MOSSE, CSRT) in openCV File YOLOv3 weight can be downloaded

Ngoc Quyen Ngo 2 Mar 27, 2022
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation （ICCV2021）

Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad

DV Lab 29 Nov 21, 2022
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (NeurIPS 2021)

VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin

Mingyu Ding 36 Sep 20, 2022
A project which aims to protect your privacy using inexpensive hardware and easily modifiable software

Protecting your privacy using an ESP32, an IR sensor and a python script This project, which I personally call the "never-gonna-catch-me-in-the-act-ev

8 Oct 10, 2022
Official implementation of the paper "Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering"

Light Field Networks Project Page | Paper | Data | Pretrained Models Vincent Sitzmann*, Semon Rezchikov*, William Freeman, Joshua Tenenbaum, Frédo Dur

Vincent Sitzmann 130 Dec 29, 2022
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

Hengrui Zhang 44 Nov 27, 2022
This Deep Learning Model Predicts that from which disease you are suffering.

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

Jai Viral Doshi 0 Jan 20, 2022
Face recognition. Redefined.

FaceFinder Use a powerful CNN to identify faces in images! TABLE OF CONTENTS About The Project Built With Getting Started Prerequisites Installation U

BleepLogger 20 Jun 16, 2021