A bilevel optimization framework with normalizing flows recovers the latent obstacle and optimal trajectories in mean-field games from partial trajectory data, achieving about 0.1 relative L2 error even with fewer than 100 trajectories.
Partial differential equation models in macroeconomics.Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 372(2028):20130397, 2014
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Joint Inference of Trajectory and Obstacle in Mean-Field Games via Bilevel Optimization
A bilevel optimization framework with normalizing flows recovers the latent obstacle and optimal trajectories in mean-field games from partial trajectory data, achieving about 0.1 relative L2 error even with fewer than 100 trajectories.