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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.

Spring 2023 Op Research - Computer Science E4529 section 001
Reinforcement Learning

Call Number 15218
Day & Time
TR 5:40pm-6:55pm
524 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Farid Alizadeh
Method of Instruction In-Person
Course Description Markov Decision Processes (MDP) and Reinforcement Learning (RL) problems. Reinforcement Learning algorithms including Q-learning, policy gradient methods, actor-critic method. Reinforcement learning while doing exploration-exploitation dilemma, multi-armed bandit problem. Monte Carlo Tree Search methods, Distributional, Multi-agent, and Causal Reinforcement Learning. 
Web Site Vergil
Department Industrial Engineering and Operations Research
Enrollment 26 students (55 max) as of 9:06PM Thursday, March 23, 2023
Subject Op Research - Computer Science
Number E4529
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20231ORCS4529E001

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SIS update 03/23/23 21:06    web update 03/23/23 21:18