TACTIC

TACTIC is a preventive simulation framework designed to model and analyze protest dynamics before they unfold in real space. The project focuses on identifying critical situations early, allowing potential conflicts to be anticipated and mitigated rather than merely reacted to.

At its core, TACTIC uses scenario-based modeling to simulate how protests evolve under varying spatial, social, and tactical conditions. Users define environments, actors, and constraints, after which the system runs multiple simulation cycles to explore how different configurations influence crowd behavior, movement patterns, and points of escalation. Rather than predicting a single outcome, the system exposes ranges of possible developments and highlights structural vulnerabilities within a given setup.

To ground the simulations in real-world behavior, the models were trained using reconstructed data from historical protest recordings. These recordings were analyzed and transformed into spatial and temporal representations of movement, interaction, and response. By learning from past events, the system captures recurring dynamics that inform how similar situations may evolve in the future.

The project was realized as a full prototype, combining a custom web-based interface with underlying simulation and learning models. Together, they form a tool for exploring preventive strategies, testing spatial interventions, and understanding how conflicts emerge and escalate within urban environments before they occur.