Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises

no code implementations • Physics and Society (physics.soc-ph); Computers and Society (cs.CY) 2020 • Chao Fan, Xiangqi Jiang, Ali Mostafavi

The objective of this study is to propose and test an adaptive reinforcement learning model that can learn the patterns of human mobility in a normal context and simulate the mobility during perturbations caused by crises, such as flooding, wildfire, and hurricanes.

reinforcement-learning Reinforcement Learning (RL)