212 citations · 568 across the 48 of their papers we have counts for
10 papers · 1 filter
A Neural Network Approach Applied to Multi-Agent Optimal Control
Derek Onken, Levon Nurbekyan, Xingjian Li +3
We propose a neural network approach for solving high-dimensional optimal control problems. In particular, we focus on multi-agent control problems with obstacle and collision avoi…
Wasserstein-based Projections with Applications to Inverse Problems
Howard Heaton, Samy Wu Fung, Alex Tong Lin +2
Inverse problems consist of recovering a signal from a collection of noisy measurements. These are typically cast as optimization problems, with classic approaches using a data fid…
A mean field game inverse problem
Lisang Ding, Wuchen Li, Stanley Osher +1
Mean-field games arise in various fields including economics, engineering, and machine learning. They study strategic decision making in large populations where the individuals int…
Controlling Propagation of epidemics via mean-field control
Wonjun Lee, Siting Liu, Hamidou Tembine +2
The coronavirus disease 2019 (COVID-19) pandemic is changing and impacting lives on a global scale. In this paper, we introduce a mean-field game model in controlling the propagati…
A Hamilton-Jacobi Formulation for Time-Optimal Paths of Rectangular Nonholonomic Vehicles
Christian Parkinson, Andrea L. Bertozzi, Stanley Osher
We address the problem of optimal path planning for a simple nonholonomic vehicle in the presence of obstacles. Most current approaches are either split hierarchically into global…
A Model for Optimal Human Navigation with Stochastic Effects
Christian Parkinson, David Arnold, Andrea L. Bertozzi +1
We present a method for optimal path planning of human walking paths in mountainous terrain, using a control theoretic formulation and a Hamilton-Jacobi-Bellman equation. Previous…