Agent Based Modeling Training Courses - Slovakia

Digital Twins are virtual representations or replicas that can be used to create simulations to predict how a product or process will perform.

This instructor-led, live training (online or onsite) is aimed at anyone who wishes to learn how to use Digital Twin in monitoring and analyzing products and processes before building and deploying the actual product.

By the end of this training, participants will be able to:

• Learn and understand the fundamental concepts of Digital Twin.
• Understand the Digital Twin types and life cycle.
• Use Digital Twin to effectively manage research data and design models.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Mesa is a Python framework for creating agent-based models (ABM). Mesa aims to provide an alternative to NetLogo, Repast, and MASON. Agent based modeling allows investigators in the fields of biology, social sciences, network, business, etc. to simulate the actions and interactions of autonomous agents in order to evaluate their effects on their environment.

This instructor-led, live training (online or onsite) is aimed at investigators who wish to use Mesa to create Agent Based Models in a Python environment.

By the end of this training, participants will be able to:

• Install and configure the development environment needed to start modeling in Python.
• Quickly create an agent-based model using Mesa's built-in core components.
• Expand the complexity of the model.
• Visualize agent activity in real-time inside a 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.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

NetLogo is one of the most famous and powerful simulation environments for agent-based modeling. NetLogo is both a development environment and a domain specific language for agent-based modelling.

This instructor-led, live training (online or onsite) is aimed at investigators who wish to use NetLogo to create Agent Based Models (ABM).

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.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Purpose

Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling complex systems composed of interacting, autonomous ‘agents’. Agents have behaviours, often described by simple rules, and interactions with other agents, which in turn influence their behaviours. By modelling agents individually, the full effects of the diversity that exists among agents in their attributes and behaviours can be observed as it gives rise to the behaviour of the system as a whole. The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation libraries that have collectively been under continuous development for over 10 years. This four day course explains in detail how to create simulation for agent-based systems using the Repast environment.

Course Objectives

1. Introduce participants to principles and concepts of agent-based modeling and simulation.
2. Develop participants’ capacity to read and understand agent modeling programming code.
3. Equip participants with knowledge, so they understand the importance of accurate and precise modeling.
4. Increase the participants’ understanding of systems of their own using the Agent-based simulation.
5. Develop a better capacity to use and code agent-based systems using repast, reLogo.

Methodology

The course models a variety of effective training methodologies including demonstration, practice, discussion, brain-storming, case studies, visualization and presentation. Once participants have gained an understanding of industrial modeling and simulation, they can use this knowledge in developing their own ABMS systems.