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How mobility assumptions change epidemic dynamics in a city-scale agent model
US & West ·
Using a synthetic population of one million agents in an urban setting, the study compares five mobility models differing in activity patterns and destination choice. It shows how mobility simplifications affect emergent contact networks and epidemic outcomes.
Why it matters
Quantifies how behavioural assumptions bias the results of a large-scale simulation model.
arXiv:2610.28907v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) offers a principled way of populating simulated economies with many heterogeneous decision makers.
arXiv:2604.04455v3 Announce Type: replace Abstract: Nonlinear underactuated systems such as two-wheeled inverted pendulums (TWIPs) exhibit a limited region of attraction (RoA), which defines the set of initial conditions from which the closed-loop system converges to the equilibrium.
The same TAdviser item: the generative AI market reached 58 billion rubles in 2025, with 44 billion corporate. Measurable results are becoming the key criterion, while most projects remain pilots due to integration, data quality, security and cost issues.
