ORIE 6590

Last Updated

  • Schedule of Classes - September 9, 2021 7:14PM EDT
  • Course Catalog - September 9, 2021 7:15PM EDT

ORIE 6590
Approximate Dynamic Programming and Reinforcement Learning

Course information provided by the 2020-2021 Catalog.

This course develops theories and algorithms for optimal sequential decision making under uncertainty. The emphasis will be on approximate algorithms to deal with large-scale decision models that can be highly uncertain. Various bounding techniques in recent literature will be covered. The course will intersect with traditional topics such as Markov decision processes, reinforcement learning, and bandit problems.


Prerequisites/Corequisites Prerequisite: ORIE 6500 or equivalent.

When Offered Spring.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • 17773 ORIE 6590   LEC 001

  •  
    • MW Online Meeting
    • Feb 8 - May 14, 2021

    • Dai, J

      Xie, Q

  • Instruction Mode: Online

    The Wednesday session will meet every week but the Monday session will meet every other week.