
General Overview
Religion is a critical factor in demographic calculations and projections because behavior is often guided by religious belief and practice. Since religious demographic projections are used by governments, corporations, and religious organizations worldwide to create policy and influence decision-making, it’s crucial that the data sets underlying those projections be as accurate as possible.
Precise and accurate projections depend upon more than just census data. Religiosity must be measured in all its many dimensions. Through a cutting-edge, agent-based modeling and simulation framework, the MRC project aims to gain a more detailed understanding of religious and nonreligious identity and change. The project will demonstrate that computational simulation can be used to generate subtler, and therefore more useful projections.

Engineering Overview
Through a dynamic, scalable simulation platform built upon modern cloud architecture, and informed by technologies employed by leading-edge game studios, the MRC engineering team is creating real-time, complex, theory-based simulations of religious and nonreligious identity and change in the USA, Norway, and India – and time permitting, Nigeria, Chile, New Zealand, and China.
The idea is to create artificial societies with cognitively plausible and behaviorally believable AI agents, and then measure the change in religiosity over time in those artificial societies. This approach advances the field of human simulation by producing a standard, computable model of religious cognition, emotion, and behavior.
The hybrid platform will combine thoughtfully curated commercial, off-the-shelf technologies with custom-built tools to work within the open cloud environment. This flexible, forward-thinking approach promises to set a new standard for what is possible for modeling and simulation development.
Once validated, our agent-based framework can be used as an experimental platform for testing policy ideas ethically, and inexpensively. It will lay the groundwork for future generalizable simulation deployment.
Meet the MRC Team

Saikou Diallo

Louise Salinas
