FIRST-ORDER OPTIMIZATION METHODS FOR STOCHASTIC DYNAMIC PROGRAMMING

Abstract

This project aims to study the foundation of numerical optimization algorithms for solving challenging stochastic dynamic programming problems. Stochastic dynamic programming enables sequential decision making under uncertainty, and thus supports critical DoD missions in search-and-rescue, unmanned aerial vehicle (UAV) control, and resource allocation etc. Mathematical optimization problems arising in this area are notoriously difficult due to high dimensionality, inherent nonconvexity, and unknown underlying transition models.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 20, 2023
Source ID
FA95502210447

Entities

People

  • Guanghui Lan

Organizations

  • Air Force Office of Scientific Research
  • Georgia Tech Research Corporation
  • United States Air Force

Tags

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Distributed Systems and Data Platform Development
  • Operations Research

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control