The use of mathematical/computational models is essential for understanding complex systems and increasingly widespread in the sciences. However, modeling a complex system in its entirety is often unfeasible - perhaps even undesirable - and so some simplification is inevitable. Any model focuses on some process(es) of interest while glossing over others; this doubtless influences its predictions, and yet the process of making these decisions is largely subjective. While the technical design of a particular model may be of little interest to researchers outside the specific field it relates to, the decision-making process will be comparable across all disciplines.
This workshop is aimed at researchers from disciplines as diverse as computational psychology, climate modelling, philosophy of science, and many more. We see this as an opportunity for attendees to reassess the basic assumptions of their models through the questions of researchers from different backgrounds, who will not take those assumptions for granted; a useful exercise that will doubtless pay off when explaining one’s model to reviewers, the public, and industry partners. Talks all be general enough to be understood by a diverse scientific audience, and the workshop will be a unique opportunity for modellers across disciplines to share their experience.
For full details, including programme and registration visit the Simplifying Assumptions website