ORCS E4529

Reinforcement Learning

Columbia University in the City of New York · UGRD · Fall 2026

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g., familiarity with linear and convex optimization, gradient descent, basic algorithm design constructs, familiarity with programming in python. 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

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Class #columbia_in_city_new_york-ORCSE4529Fall 2026UGRD3.00 credits
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