# 03 @ Using an AI-powered buddy for designing innovative ABMs
 
Credits: Written by Peer-Olaf Siebers
 
After working on it for over a year, my paper Exploring Conversational AI for Agent-Based Social Simulation Design has finally been published in the Journal of Artificial Societies and Social Simulation. It explores the use of ChatGPT for conceptual modelling and the co-creation of agent-based models. To promote the paper, I gave a presentation at the LLM4ABM Special Interest Group meeting yesterday. Below, you can find links to the presentation slides, the published paper, and a GitHub repository containing additional resources. The repository is a dynamic resource and over the summer I will add further examples, an updated script, and other resources. You are welcome to add your examples to the repository as well :-).
 
Abstract: ChatGPT, the AI-powered chatbot with a massive user base of hundreds of millions, has become a global phenomenon. However, the use of Conversational AI Systems (CAISs) like ChatGPT for research in the field of Social Simulation is still limited. Specifically, there is no evidence of its usage in Agent-Based Social Simulation (ABSS) model design. This paper takes a crucial first step toward exploring the untapped potential of this emerging technology in the context of ABSS model design. The research presented here demonstrates how CAISs can facilitate the development of innovative conceptual ABSS models in a concise timeframe and with minimal required upfront case-based knowledge. By employing advanced prompt engineering techniques and adhering to the Engineering ABSS framework, we have constructed a comprehensive prompt script that enables the design of conceptual ABSS models with or by the CAIS. A proof-of-concept application of the prompt script, used to generate the conceptual ABSS model for a case study on the impact of adaptive architecture in a museum environment, illustrates the practicality of the approach. Despite occasional inaccuracies and conversational divergence, the CAIS proved to be a valuable companion for ABSS modellers.
 
Back to Top
 
 
# 02 @ EABSS-2: A Software Engineer's Approach to Creating Agent-Based Models
 
Credits: Drafted by Peer-Olaf Siebers, turbocharged by ChatGPT-4o
 
Ever wondered how to build agent-based models the smart way, without the usual headaches? If you are a fan of modelling human behaviour, testing policy impacts, or just love crafting digital societies, then you're going to love what's new in the world of simulation frameworks. Meet EABSS-2, the fresh and improved version of the Engineering Agent-Based Social Simulations (EABSS) framework! We all know that designing agent-based models can be a complex (sometimes messy) process, especially when working in teams. That's where EABSS-2 steps in to save the day. It is more than just a tool; it's a guided workflow that helps both solo and collaborative creators turn great ideas into working simulations with far less friction.

Although EABSS-2 is still a work in progress, a preview and supplementary material are already available for those keen to take a first look. The framework's new features are introduced in an upcoming journal paper, which offers a detailed walkthrough of the improvements and a case study showcasing them in action. The official release is planned for December 2025, so stay tuned for more updates.
 
  • EABSS Toolkit Website: link
  • EABSS-2 Survival Pack: link
So, what's new and exciting in EABSS-2?
  • Clarity from the Start: The biggest new feature? A brand-new first step: Define Problem Statement. It might sound simple, but it's a game-changer. By starting with a clear articulation of what you're studying and why, you massively reduce confusion later down the line. No more vague goals or misaligned assumptions!
  • Smarter Reuse, Less Rework: The second major upgrade is an instructional information reuse schema (we know, sounds fancy – but it's super helpful). This guides you to pull forward useful insights from earlier steps, so you're not constantly reinventing the wheel. Plus, it checks for any missing info in real time, like a helpful co-pilot reminding you to dot your i's and cross your t's.
EABSS-2 isn't just a framework, it's a thoughtful redesign focused on making simulation-building more accessible, rigorous, and even enjoyable. Whether you're a student, a researcher, or just simulation-curious, this update could make your next social modelling project your smoothest yet. Let's build smarter societies, one simulation at a time!
 
Back to Top
 
 
# 01 @ From Roots to Horizons: The Evolution of My ABM Research Journey
 
Credits: Words by Peer-Olaf Siebers. Title crafted by ChatGPT-4o
 
My ABM related research can be subsumed under the umbrella of 'collaboratively creating artificial labs for better understanding current and future human and mixed human/robot societies'. I am a strong advocate of Computational ABM. Before the era of Large Language Models (LLMs) started, I focused on applying software engineering methods and techniques to develop conceptual agent-based models. My current research is focused on how LLMs can be used at any stage of the ABM study lifecycle.

For more information, please take a look at the following posters:
  • Poster 1: Everything you always wanted to know about Dr Siebers (academic details only :) - 2nd Edition
  • Poster 2: Exploring the Role of Generative AI in Advancing Agent-Based Model Design and Implementation
 
Back to Top