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Course Information

Course Name
Turkish İşletme Uygulamaları için Pekiştirilmiş Öğrenme
English Reinforcement Learning for Business Applications
Course Code
VIA 529E Credit Lecture
(hour/week)
Recitation
(hour/week)
Laboratory
(hour/week)
Semester -
3 3 - -
Course Language English
Course Coordinator Mehmet Yasin Ulukuş
Mehmet Yasin Ulukuş
Course Objectives 1. To introduce theory of Markov decision problems and reinforcement learning
2. To introduce different reinforcement learning techniques
3. To implement different reinforcement learning techniques to various problems
4. To introduce performance evaluation of reinforcement learning techniques
Course Description This course provides an introduction to some of the foundational ideas of reinforcement learning, including Markov decision processes, value functions, Monte Carlo estimation, dynamic programming, temporal difference learning, eligibility traces, and function approximation. However, we will also cover additional material drawn from the latest deep Reinforcement Learning literature. Programming assignments and projects will require implementing and testing these techniques for various problems.
Course Outcomes
Pre-requisite(s)
Required Facilities
Other
Textbook
Other References
 
 
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