Automatic Gradient Estimation for Calibrating Crowd Models with Discrete Decision Making

arXiv:2404.04678v1 Announce Type: new
Abstract: Recently proposed gradient estimators enable gradient descent over stochastic programs with discrete jumps in the response surface, which are not covered by automatic differentiation (AD) alone. Although these estimators' capability to guide a swift local search has been shown for certain problems, their applicability to models relevant to real-world applications remains largely unexplored. As the gradients governing the choice in candidate solutions are calculated from sampled simulation trajectories, the optimization procedure bears similarities to metaheuristics …

abstract arxiv capability cs.lg cs.ma decision decision making differentiation gradient guide making search stochastic surface swift type