OPTIMAL CONTROL PROBLEM

Abstract

This research paper delves into optimizing the Average Value at Risk (AVaR) using Approximate Dynamic Programming (ADP) in the context of optimal control problems. The study focuses on comparing different numerical optimization methods to achieve that. The methods include Bisection, Gradient Descent, Simulated Annealing, and Conjugate Gradient. The purpose is to assess their accuracy and computational effectiveness in optimizing AVaR function within discrete time, finite horizon settings.