Online Agent Based Modeling Training in US

This instructor-led, live training in [location] (online or onsite) is designed for government employees and professionals who wish to learn how to utilize Digital Twin technology for monitoring and analyzing products and processes before the actual deployment of these items. By the end of this training, participants will be able to: - Understand the core principles and fundamental concepts of Digital Twin. - Gain knowledge about the various types of Digital Twins and their lifecycle. - Effectively manage research data and design models using Digital Twin technology for government applications.

This instructor-led, live training in US (online or onsite) is aimed at investigators who wish to use Mesa to create Agent-Based Models in a Python environment for government. By the end of this training, participants will be able to: - Install and configure the development environment necessary to begin modeling in Python. - Efficiently create an agent-based model using Mesa’s built-in core components. - Enhance the complexity of the model as needed. - Visualize agent activity in real-time within a web browser. - Analyze the results of the model interactively using Python data analysis tools. - Integrate the model with other Python systems, such as machine learning applications.

This instructor-led, live training in US (online or onsite) is aimed at investigators who wish to use NetLogo to create Agent Based Models (ABM) for government applications. By the end of this training, participants will be able to: - Install NetLogo. - Develop an agent-based model. - Visualize agent activity. - Analyze the results of the model. - Test and document the agent-based simulation model.

The Repast Suite is a collection of advanced, free, and open-source agent-based modeling and simulation libraries that have been under continuous development for over a decade. This four-day course, offered either online or on-site, provides a comprehensive overview of how to create simulations for agent-based systems using the Repast environment. ### Course Objectives 1. Introduce participants to the fundamental principles and concepts of agent-based modeling and simulation. 2. Enhance participants' ability to read and interpret agent modeling programming code. 3. Equip participants with the knowledge necessary to understand the importance of accurate and precise modeling, particularly for government applications. 4. Improve participants’ understanding of their own systems through the use of agent-based simulations. 5. Develop a stronger capacity to utilize and code agent-based systems using Repast and reLogo.