A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

Related tags

Deep Learningopenstreetmapcellular-automatatraffic-analysistopology-optimization3d-networktraffic-simulationmulti-agent-simulationdrone-simulation
Overview

Codacy Badge

AMAZ3DSim

AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery capacities, travel time and travelled distance of the agents and the loudness the network links experience. AMAZ3DSim is suitable for 3D network optimization tasks. AMAZ3DSim simulation of OSM Darmstadt scenario

Installation

Use the package manager pip to install foobar.

sudo apt install python3.8

pip install click
pip install tkinter

Usage

To start AMAZ3DSim with default settings

python3.8 CommandLineInterface.py

To open a small help doc listing the parameters of the CommandLineInterface.py

python3.8 CommandLineInterface.py --help

A full command specified all of the following paramters

python3.8 CommandLineInterface.py --in-file /path/to/scenario.xml --out-file /path/to/output.xml --configfile /path/to/config.xml --random False

If an argument is left out, a standard value is used.

Configuration

A fully commented example configuration is available under

config/config.xml

which is also the standard configuration.

Input interface of the simulator

To simulate your own network, create your own scenario.xml file. A scenario.xml contains the network, the agents and the delivery orders to be fulfilled.

Example scenario.xml files are available in the input folder.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

You might also like...
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)

nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom

Qiujie (Jay) Dong 2 Oct 31, 2022
An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.
An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.

ImageCompressionSimulation An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects o

James Park 1 Dec 11, 2021
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Google Research 258 Dec 29, 2022
A simple and lightweight genetic algorithm for optimization of any machine learning model

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Allan Barcelos 8 Aug 10, 2022
Matlab Python Heuristic Battery Opt - SMOP conversion and manual conversion

SMOP is Small Matlab and Octave to Python compiler. SMOP translates matlab to py

Tom Xu 1 Jan 12, 2022
Lux AI environment interface for RLlib multi-agents
Lux AI environment interface for RLlib multi-agents

Lux AI interface to RLlib MultiAgentsEnv For Lux AI Season 1 Kaggle competition. LuxAI repo RLlib-multiagents docs Kaggle environments repo Please let

Jaime 12 Nov 7, 2022
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Katherine Crowson 53 Dec 29, 2022
Lightweight mmm - Lightweight (Bayesian) Media Mix Model

Lightweight (Bayesian) Media Mix Model This is not an official Google product. L

Google 342 Jan 3, 2023
A multi-entity Transformer for multi-agent spatiotemporal modeling.
A multi-entity Transformer for multi-agent spatiotemporal modeling.

baller2vec This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec: A Multi-Entity Transformer For Multi-Agent Spatiotempor

Michael A. Alcorn 56 Nov 15, 2022
Comments
  • Error in scenarioParser

    Error in scenarioParser

    Starting the CommandLineInterface on default settings causes an error (see screenshot). The problem stays also with the simple scenario, but without lines 157-162 in ScenarioParser, it works.

    issue
    opened by JuliaBlome 3
  • Overloaded link lets agents freely travel despite capacity

    Overloaded link lets agents freely travel despite capacity

    An input scenario that places too many agents on a link should be handled realistically by the simulator.

    e.g. 50 agents can be placed on a capacity 1 link, but then only 1 agent should be able to move

    As of now, all agents move freely on the first link they are generated on.

    opened by danieldeer 1
Releases(v1.0.0)
Owner
Daniel Hirsch
Software Engineer @ Telespazio 🛠 M.Sc. Electrical Engineering and Information Technology (TU Darmstadt) 📀
Daniel Hirsch
GitHub Repository
🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)"

PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi

Vitaliy Hramchenko 58 Dec 19, 2022
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual

FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P

Sauradip Nag 14 Dec 09, 2022
PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer

Official code Cross-Covariance Image Transformer (XCiT)

Facebook Research 605 Jan 02, 2023
Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Oral)

Pixel-Perfect Structure-from-Motion (ICCV 2021 Oral) We introduce a framework that improves the accuracy of Structure-from-Motion by refining keypoint

Computer Vision and Geometry Lab 831 Dec 29, 2022
Google-drive-to-sqlite - Create a SQLite database containing metadata from Google Drive

google-drive-to-sqlite Create a SQLite database containing metadata from Google

Simon Willison 140 Dec 04, 2022
Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders"

DECA Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders". All the code is writte

23 Dec 01, 2022
Dynamic Head: Unifying Object Detection Heads with Attentions

Dynamic Head: Unifying Object Detection Heads with Attentions dyhead_video.mp4 This is the official implementation of CVPR 2021 paper "Dynamic Head: U

Microsoft 550 Dec 21, 2022
OoD Minimum Anomaly Score GAN - Code for the Paper 'OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary'

OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary Out-of-Distribution Minimum Anomaly Score GAN (OMASGAN) C

- 8 Sep 27, 2022
Python implementation of Wu et al (2018)'s registration fusion

reg-fusion Projection of a central sulcus probability map using the RF-ANTs approach (right hemisphere shown). This is a Python implementation of Wu e

Dan Gale 26 Nov 12, 2021
A deep-learning pipeline for segmentation of ambiguous microscopic images.

Welcome to Official repository of deepflash2 - a deep-learning pipeline for segmentation of ambiguous microscopic images. Quick Start in 30 seconds se

Matthias Griebel 39 Dec 19, 2022
links and status of cool gradio demos

awesome-demos This is a list of some wonderful demos & applications built with Gradio. Here's how to contribute yours! 🖊️ Natural language processing

Gradio 96 Dec 30, 2022
Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

Phil Wang 22 Oct 28, 2022
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning

Datasets | Website | Raw Data | OpenReview SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning Christopher

67 Dec 17, 2022
A Python library for generating new text from existing samples.

ReMarkov is a Python library for generating text from existing samples using Markov chains. You can use it to customize all sorts of writing from birt

8 May 17, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

Meta Research 283 Dec 30, 2022
Towards Multi-Camera 3D Human Pose Estimation in Wild Environment

PanopticStudio Toolbox This repository has a toolbox to download, process, and visualize the Panoptic Studio (Panoptic) data. Note: Sep-21-2020: Curre

335 Jan 09, 2023
Deep Reinforcement Learning for Multiplayer Online Battle Arena

MOBA_RL Deep Reinforcement Learning for Multiplayer Online Battle Arena Prerequisite Python 3 gym-derk Tensorflow 2.4.1 Dotaservice of TimZaman Seed R

Dohyeong Kim 32 Dec 18, 2022
A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.

Image Classification in Python Implementing image classification in Flask using Keras. The VGG16 is a convolution neural network model architecture th

Gerald Maduabuchi 19 Dec 12, 2022
Pytorch implementation of Feature Pyramid Network (FPN) for Object Detection

fpn.pytorch Pytorch implementation of Feature Pyramid Network (FPN) for Object Detection Introduction This project inherits the property of our pytorc

Jianwei Yang 912 Dec 21, 2022
[IEEE Transactions on Computational Imaging] Self-Gated Memory Recurrent Network for Efficient Scalable HDR Deghosting

Few-shot Deep HDR Deghosting This repository contains code and pretrained models for our paper: Self-Gated Memory Recurrent Network for Efficient Scal

Susmit Agrawal 4 Dec 29, 2021