CSCE-642
Reinforcement Learning

Fall 2025

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Participation

Please ensure that you meet the course's expected background knowledge. If you are unsure, contact the course staff for clarification. Registered students are required to participate in:

  • Online quizzes available on the course's Canvas website.
  • Programming assignments.
  • Original research as part of a course project.

General questions, comments, and discussions should be posted on the course Canvas discussion board. Please refrain from emailing the course staff with general inquiries, as such messages will be redirected to the discussion board. You are encouraged to help your peers by responding to posted questions; students who provide exceptionally helpful contributions may receive extra credit.


Text Books

  • Reinforcement Learning: An Introduction
  • Reinforcement Learning: State-of-the-Art
  • Artificial Intelligence: A Modern Approach
  • Deep Learning

Lectures

Lecture #SlidesLecture
1Introduction.pptxRecording
2Multi-Armed Bandit.pptxRecording
3MDPs.pptxRecording
4MDPs.pptx (continue)Recording
5Monte-Carlo Methods.pptxRecording
6Monte-Carlo Methods.pptx (continue)Recording
7Temporal Difference.pptxRecording
8Bootstrapping.pptxRecording
9Model-based RL.pptxRecording
10Prediction with Approximation.pptxRecording
11DNN Approximation.pptxRecording
12Control with Approximation.pptxRecording
13Eligibility Traces.pptxRecording
14Deep Q-Learning.pptxRecording
15No Class
16Policy Gradient.pptxRecording
17Actor Critic.pptxRecording
18Trust Regions.pptxRecording
19Trust Regions.pptx (continue)Recording
20Soft Actor-Critic.pptxRecording
21Soft Actor-Critic.pptx (continue)Recording
22Transfer Learning.pptxRecording
23Transfer Learning.pptx (continue)Recording
24Immitation Learning.pptxRecording
25Derivative Free.pptxRecording
26Derivative Free.pptx (continue)Recording
27Curriculum Learning.pptxRecording
28Curriculum Learning.pptx (continue)Recording

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