Advancing simulation experimentation capabilities with runtime interventions

Experimentation is a critical capability of simulations that allows one to test different scenarios safely and cost-effectively. In particular, agent-based simulations have been used in experimenting with different policy options to aid decision makers. Highly utilized experimentation methods such as parameter sweeping aim to explore the relationship between the initial parameter values (i.e., input) and simulation results (i.e., outputs). Experimentation, which involves changes of simulation states on-the-fly, is often conducted ad-hoc and entails manual code adjustments which are time consuming and error-prone. In this paper, we present a framework that facilitates intervening in a running simulation to change simulation states in a semi-automated manner so that a simulation user can explore alternative worlds. In our framework, such an intervention is implemented using an injection mechanism. The framework allows the user to weigh different policy options rapidly with minimal effort. We illustrate its use in an urban agent-based model.