Format:
1 Online-Ressource (23 Seiten)
ISSN:
1951-6355
,
1951-6355
Content:
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.
Content:
Peer Reviewed
In:
Heidelberg : Springer, 230,16-17, Seiten 3249-3271, 1951-6355
Language:
English
DOI:
10.1140/epjs/s11734-021-00191-0
URN:
urn:nbn:de:kobv:11-110-18452/27686-4
URL:
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