Course Description
Do you have a compelling theory on how science works that requires exploratory testing, but you find it impossible to test empirically? Have you ever wondered how the mechanisms of scientific inquiry would function under entirely different conditions—such as alternative funding structures or communication norms?
This workshop introduces theoretical Agent-Based Models (ABM) as a logic engine for the Science of Science. We discuss simulations as transparent tools for theory-building and exploratory testing. By formalizing our verbal hypotheses into computational agents, we can investigate the hidden causal structures of scientific inquiry—asking how specific institutional or social mechanisms produce macro-level epistemic outcomes. The session is divided into two distinct parts:
Part 1: Idealized Models of Science
The first half is designed for those new to modeling in the philosophy of science. We will explore classic models (such as the Zollman effect and epistemic landscapes), focusing on their underlying assumptions and how they have been used to shape our understanding of scientific inquiry. We will discuss why “building” a phenomenon in a highly idealized, stripped-back environment is often more insightful than trying to predict it in all its real-world complexity.
Part 2: ABMs as Open Science
The second half focuses on how we can use models to ensure they function as reliable communal assets. We will discuss the philosophy of models through the lens of Open Science. If the goal of an ABM is its epistemic function (e.g., to prove a logical possibility), how must we communicate it so that others can evaluate, criticize, and extend it? We will discuss a framework for presenting and describing models—moving beyond the code to the transparent communication of the model’s logic—ensuring that your theoretical work is as robust, testable, and reusable as any empirical dataset.
Prerequisites
This workshop is conceptual. No experience in programming or advanced mathematics is required.
Reading Materials
Optional
- Epstein, J. M. (2008). Why Model? – On the diverse goals of modeling beyond prediction. https://www.jasss.org/11/4/12.html
- Weatherall, J. O., O’Connor, C., & Bruner, J. P. (2020). How to Beat Science and Influence People: Policymakers and Propaganda in Epistemic Networks – A study on how “industrial propagandists” can manipulate scientific consensus without ever fabricating data, simply by sharing biased samples of real results. https://www.journals.uchicago.edu/doi/10.1093/bjps/axy062
- Šešelja, D. (2022). Exploring Scientific Inquiry via Agent-Based Modeling. – A methodological guide on how to use ABMs responsibly to gain insights into the philosophy of science. https://doi.org/10.1162/posc_a_00382
Capacity
This course has a maximum capacity of 35 participants.
Time and Location
This workshop will be held on-site only at Eindhoven University of Technology on May 27, 2026. Details will be provided to all attendees over email after registration for the workshop.
Workshops start from 9:30 to 16:30 with a lunch break from 12:30 to 13:30. Lunch will not be provided but can be purchased at the university canteen or the on-campus supermarket.
Registration
To register for this workshop, please complete the following form by May 18. Note that your registration will be considered finalized only after receiving a confirmation email. The registration link will remain open after this date if spots are still available.
Instructor
Dr. Matteo Michelini
Matteo Michelini is an adjunct professor at the University of Milan. His research focuses on applying agent-based models (ABMs) to philosophical problems, particularly on how epistemic practices that may be detrimental at the individual level can nonetheless benefit the community as a whole.