ORIE 6590

ORIE 6590

Course information provided by the 2018-2019 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 Fall.

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Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • 17222 ORIE 6590   LEC 001

  • Instruction Mode: In Person