jueewo | labs

This page shows a collection of our project engagements and ongoing research. We are posting here regularly, so please keep coming back and check for updates.

For more information visit >> jueewo.com

Go for Agent-based Simulation

using Go (golang)

Here we are using the programming language Go (golang.org) to implement a framework for agent-based simulation. Agent-based simulation is one of my major research area and I’ve used a wide range of tools to implement and run the simulation models. NetLogo AnyLogic Python (own framework implementation) … With the language Go on the rise and given it’s performance and toolset, I’m going to give it a try and to reimplement the Python code base to Go. [Read More]

Blockchain & DApps

a new development paradigm

Blockchain - A Brave New World These days, mid of 2018, the blockchain, cryptocurrencies, initial coin offers (ICO), decentralized applications (DApps), artificial intelligence are the new trending keywords which can be found in many tech-related articles all over the media. Our main question is how these trends and new technologies are influencing business, media, and society over the next years. Blockchain Applications Blockchain infrastructure has matured and has been published as open-source projects. [Read More]

WebConjoint

Conjoint Analysis

WebConjoint WebConjoint measures preferences implicitly. This is crucial when (product) features need to be traded mutually. Many real-world decisions require to trade one feature for another, e.g. high quality and low price are precluding each other, so it’s necessary to trade quality for price or vice versa. Traditional measurements (e.g. surveys, interviews, etc.) are testing features separately (itemized). In the case of related features, traditional tools produce incorrect results. The interactive tool WebConjoint is using a joint measurement of how the features of products and services are mutually traded. [Read More]

Agent-based Policy Simulation

EU-funded [FP7] project

Agent-based simulation of policy making in highly interactive dynamic systems This project is introducing a dynamic simulation framework to simulate and optimize decisions and policies. A hybrid (continuous & discrete) simulation core is used for the calculation of the interactive effects of heterogeneous actors. After the system is calibrated using learning algorithms, various scenarios are captured in a data model. The calibrated system is used as a decision support system for optimal policy making. [Read More]

Disaster Relief Simulation

FARMS

Disaster Relief Simulation The research project ‘Disaster Relief Simulation’ is dealing with the issue of resource allocation, information asymmetry and collaborative planning at the site of emergencies. The focus is to develop optimal decision-making strategies using a theoretic simulation approach. This simulation allows to derive and evaluate different communication and management strategies. The results should help to set up and calibrate an information system which is tracking the resources on a disaster site and should provide relevant information to the different actors. [Read More]

Artificial Consumer Markets

an agent-based approach

Artificial Consumer Markets The research project “Artificial Consumer Markets” is modeling the dynamic of business decisions in consumer markets. The research topics are covering a comprehensive range of strategic decision making, from product development to marketing and finance. focusing on dynamic interaction effects on markets. This approach allows the simulation of the trade-off between different (contradicting) strategic options and business decision. Research Topics Market entry strategies (defender model, Hauser & Shugan) Diffusion of product information (word-of-mouth) Local vs. [Read More]