8166 2021 eng 3249 3271 230 article 0 2021-06-18 2021-06-18 -- Agent-based models are a natural choice for modeling complex social systems. In such models simple stochastic interaction rules for a large population of individuals on the microscopic scale can lead to emergent dynamics on the macroscopic scale, for instance a sudden shift of majority opinion or behavior. Here we are introducing a methodology for studying noise-induced tipping between relevant subsets of the agent state space representing characteristic configurations. Due to a large number of interacting individuals, agent-based models are high-dimensional, though usually a lower-dimensional structure of the emerging collective behaviour exists. We therefore apply Diffusion Maps, a non-linear dimension reduction technique, to reveal the intrinsic low-dimensional structure. We characterize the tipping behaviour by means of Transition Path Theory, which helps gaining a statistical understanding of the tipping paths such as their distribution, flux and rate. By systematically studying two agent-based models that exhibit a multitude of tipping pathways and cascading effects, we illustrate the practicability of our approach. Eur. Phys. J. Spec. Top. 2103.02883 10.1140/epjs/s11734-021-00191-0 publish yes Luzie Helfmann Luzie Helfmann Jobst Heitzig Péter Koltai Jürgen Kurths Christof Schütte Schütte, Christof Modeling and Simulation of Complex Processes Stability and Tipping in Social Systems