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.

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

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

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

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

Matlab Python Heuristic Battery Opt - SMOP conversion and manual conversion

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

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

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

Lightweight mmm - Lightweight (Bayesian) Media Mix Model

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

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

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 πŸ›  M.Sc. Electrical Engineering and Information Technology (TU Darmstadt) πŸ“€
Daniel Hirsch
Exploring the link between uncertainty estimates obtained via "exact" Bayesian inference and out-of-distribution (OOD) detection.

Uncertainty-based OOD detection Exploring the link between uncertainty estimates obtained by "exact" Bayesian inference and out-of-distribution (OOD)

Christian Henning 1 Nov 05, 2022
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks

ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20

Shirley (Ying-Xin) Wu 47 Dec 16, 2022
SmallInitEmb - LayerNorm(SmallInit(Embedding)) in a Transformer to improve convergence

SmallInitEmb LayerNorm(SmallInit(Embedding)) in a Transformer I find that when t

PENG Bo 11 Dec 25, 2022
To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

Kunal Wadhwa 2 Jan 05, 2022
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip

Junpeng Jing 67 Nov 22, 2022
LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

LightningFSL: Few-Shot Learning with Pytorch-Lightning In this repo, a number of pytorch-lightning implementations of FSL algorithms are provided, inc

Xu Luo 76 Dec 11, 2022
Deep Compression for Dense Point Cloud Maps.

DEPOCO This repository implements the algorithms described in our paper Deep Compression for Dense Point Cloud Maps. How to get started (using Docker)

Photogrammetry & Robotics Bonn 67 Dec 06, 2022
Codes for the ICCV'21 paper "FREE: Feature Refinement for Generalized Zero-Shot Learning"

FREE This repository contains the reference code for the paper "FREE: Feature Refinement for Generalized Zero-Shot Learning". [arXiv][Paper] 1. Prepar

Shiming Chen 28 Jul 29, 2022
A framework to train language models to learn invariant representations.

Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co

6 Nov 16, 2022
[SIGGRAPH Asia 2021] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning.

DeepVecFont This is the homepage for "DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning". Yizhi Wang and Zhouhui Lian. WI

Yizhi Wang 17 Dec 22, 2022
Source code for the BMVC-2021 paper "SimReg: Regression as a Simple Yet Effective Tool for Self-supervised Knowledge Distillation".

SimReg: A Simple Regression Based Framework for Self-supervised Knowledge Distillation Source code for the paper "SimReg: Regression as a Simple Yet E

9 Oct 15, 2022
A library for efficient similarity search and clustering of dense vectors.

Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any

Meta Research 18.8k Jan 08, 2023
D2LV: A Data-Driven and Local-Verification Approach for Image Copy Detection

Facebook AI Image Similarity Challenge: Matching Track β€”β€” Team: imgFp This is the source code of our 3rd place solution to matching track of Image Sim

16 Dec 25, 2022
Prefix-Tuning: Optimizing Continuous Prompts for Generation

Prefix Tuning Files: . β”œβ”€β”€ gpt2 # Code for GPT2 style autoregressive LM β”‚ β”œβ”€β”€ train_e2e.py # high-level script

530 Jan 04, 2023
Baseline and template code for node21 detection track

Nodule Detection Algorithm This codebase implements a baseline model, Faster R-CNN, for the nodule detection track in NODE21. It contains all necessar

node21challenge 11 Jan 15, 2022
PyTorch wrappers for using your model in audacity!

audacitorch This package contains utilities for prepping PyTorch audio models for use in Audacity. More specifically, it provides abstract classes for

Hugo Flores GarcΓ­a 130 Dec 14, 2022
Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021)

Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021) Introduction This is the official repository for the PyTorch implementation

165 Dec 07, 2022
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning

FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cr

Scaleout 75 Nov 09, 2022
Dashboard for the COVID19 spread

COVID-19 Data Explorer App A streamlit Dashboard for the COVID-19 spread. The app is live at: [https://covid19.cwerner.ai]. New data is queried from G

Christian Werner 22 Sep 29, 2022
FANet - Real-time Semantic Segmentation with Fast Attention

FANet Real-time Semantic Segmentation with Fast Attention Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko , Stan Sc

Ping Hu 42 Nov 30, 2022