ORIE 5570
Last Updated
- Schedule of Classes - November 21, 2024 7:58PM EST
- Course Catalog - November 21, 2024 7:07PM EST
Classes
ORIE 5570
Course Description
Course information provided by the Courses of Study 2024-2025.
The ongoing information revolution and the advent of the big data era make quantitative methods in the business context indispensable. This course introduces reinforcement learning, decision-making under uncertainty, and related algorithms through the lens of OR applications. Examples will be drawn from real-world problems in operations, revenue management, queuing, finance, transportation, healthcare, and other areas of interest. The course will cover modeling and applications, basic theory, and algorithms.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: ORIE 3300, ORIE 3500, or equivalent.
Outcomes
- Be able to formalize dynamic decision problems under uncertainty as Markov decision processes.
- Learn about finite-horizon and infinite-horizon MDPs.
- Know how to solve MDPs exactly via dynamic programming as well as know how to solve MDPs approximately via reinforcement learning.
- Learn to read the technical literature in operations research, machine learning, and control literature.
- Gain hands-on experience in implementing and applying various exact and approximate algorithms.
Regular Academic Session. Combined with: ORIE 4570
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Credits and Grading Basis
3 Credits Graded(Letter grades only)
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Class Number & Section Details
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Meeting Pattern
- MW Bill and Melinda Gates Hll 114
- Aug 26 - Dec 9, 2024
Instructors
Shafiee, S
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Additional Information
Instruction Mode: In Person
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