SYSEN 5680
Last Updated
- Schedule of Classes - June 21, 2024 12:50PM EDT
- Course Catalog - June 6, 2024 12:59PM EDT
Classes
SYSEN 5680
Course Description
Course information provided by the 2024-2025 Catalog. Courses of Study 2024-2025 is scheduled to publish mid-June.
Covers the basic models and solution approaches for individual and team decision-making problems under uncertainty and provide a unified mathematical treatment of the subject, suitable for a broad engineering audience. The material will consider optimal decision-making of systems over a finite- and an infinite-time horizon. Topics include: (1) Stochastic optimization: finite- and infinite-horizon problems with complete or partial state information, separation principle, dual control; (2) Team Theory: mathematical framework of cooperating members in which all members have the same objective yet different information; (3) Reinforcement learning: approximate dynamic programming, forward references to the approximate dynamic programming formalism, learning policies.
Permission Note Primarily for: graduate students.
Last 4 Terms Offered (None)
When Offered Spring.
Comments Knowledge of linear algebra, real analysis, and probability, especially conditional distributions, and expectations.
Regular Academic Session. Combined with: CEE 6680, SYSEN 6680
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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 Online Meeting
- Jan 21 - May 6, 2025
Instructors
Malikopoulos, A
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Additional Information
Instruction Mode: In Person
Enrollment limited to: graduate students. Undergraduates may only enroll with permission from the instructor.
Regular Academic Session. Combined with: CEE 6680, SYSEN 6680
-
Credits and Grading Basis
3 Credits Graded(Letter grades only)
-
Class Number & Section Details
-
Meeting Pattern
- Online Meeting
- Jan 21 - May 6, 2025
Instructors
Malikopoulos, A
-
Additional Information
Instruction Mode: Distance Learning-Asynchronous
Enrollment limited to: distance learning graduate students. To enroll in this class contact the department at jd648@cornell.edu to request a PIN number.
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