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401-4937-75L 2 Credits DR , MSC D-MATH

Topics on Stochastic Optimal Control

Lecturers & Examiners: Dr. Joshué Heli Ricalde Guerrero
VVZ CR n/a

Last Updated: 2026-06-01 11:30:59

Abstract

This course explores the theoretical foundations of Stochastic Optimal Control, focusing on its probabilistic framework. Key topics include the Pontryagin Maximum Principle and the Dynamic Programming Principle, with an emphasis on the backward stochastic differential equation (BSDE) approach to solving control problems under uncertainty.

Objective

By the end of the course, students will be able to: -Understand the basic structure of stochastic optimal control problems. -Analyze and systematically apply the key mathematical tools required to solve such problems.

Resources

Literature

The primary texts for the course include: - Wendell Fleming and Raymond Rishel. Deterministic and Stochastic Optimal Control. Springer Science & Business Media, Dec. 2012. - Nizar Touzi and Agnès Tourin. Optimal stochastic control, stochastic target problems, and backward SDE. Fields Institute monographs v. 29. Springer, 2013. - Jiongmin Yong and Xun Yu Zhou. Stochastic controls: Hamiltonian systems and HJB equations. Applications of mathematics 43. Springer, 1999.

General Information

Language
English
Levels
DR , MSC

Examination

Type
ungraded semester performance
pass/fail: students will be asked to participate and present selected papers

Course Components

Type Title Time & Place Hours
lecture Topics on Stochastic Optimal Control
  • Tue 13:15-14:00 (HG E 1.2)
1 h weekly

Offered In