Reinforcement Learning

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Topics and Objectives

• MDP and RL formulation
• Bellman equation
• Contraction Mapping Theorem
• Value Iteration
• Model-free vs. Model-based RL
  
• Fitted Q-Iteration
• Function approximation in RL
• Online vs. Offline RL
• Algorithms for solving MDPs

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Week 12 (Nov 11 and Nov 13)

• Nov 4: [Markov Decision Processes]
• Nov 6: [Contraction Mapping Theorem]

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Week 13 (Nov 18 and Nov 20)

• Nov 6: [Fitted Q-Iteration] [CartPole Simulator]
• Nov 8: [Policy Gradient]

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Week 14 Fall Break

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Week 15 (Nov 18 and Nov 20)

• Dec 2: [Policy Iteration and SAC]