Sarah Dean PRO
asst prof in CS at Cornell
Prof. Sarah Dean
MW 2:45-4pm
Zoom (110 Hollister Hall)
1. What is Reinforcement Learning (RL)?
2. Logistics and Syllabus
3. Types of Machine Learning (ML)
4. Markov Decision Processes (MDP)
5. Layers of Feedback
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observation
action
reward
a policy maps observation to action
design policy to achieve high reward
reaction
adaptation
observation
action
reward
AlphaGo
Robotic Manipulation
Media Feeds
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\(\theta_t-\theta_*\)
1. What is Reinforcement Learning (RL)?
2. Logistics and Syllabus
3. Types of Machine Learning (ML)
4. Markov Decision Processes (MDP)
5. Layers of Feedback
There is high demand for this course!
Course staff do not manage waitlist and enrollment.
CS enrollment policies:
https://www.cs.cornell.edu/courseinfo/enrollment
Lecture material available on Canvas regardless.
Participation is 5% of final grade, /20 points
Machine learning (e.g., CS 4780)
Basics of probability, linear algebra, and programming.
Lecture Notes and Videos*
*unless technical difficulties prevent recording
Extra Resources (not required)
RL Theory Book: https://rltheorybook.github.io/
Classic RL Book: Sutton & Barto (http://www.incompleteideas.net/book/RLbook2020.pdf)
1. What is Reinforcement Learning (RL)?
2. Logistics and Syllabus
3. Types of Machine Learning (ML)
4. Markov Decision Processes (MDP)
5. Layers of Feedback in RL
By Sarah Dean