CS 4/5789: Introduction to Reinforcement Learning

Lecture 2

Prof. Sarah Dean

MW 2:45-4pm
Zoom (110 Hollister Hall)

Agenda

 

0. Recap & Announcements

1. Markov Decision Process

2. Value and Q functions

3. Policy Evaluation

4. Approximate Policy Evaluation

5. State-Action Distribution

Announcements

 

I do not handle waitlist and enrollment.
Questions? cs-course-enroll@cornell.edu

Want to Audit? Post on Ed Discussion after Add deadline.

 

Partner finding, Feb 2, 7-9 pm
RSVP by 1/28: https://bit.ly/3qIIDaz

 

Register for participation (Canvas): PollEV.com/sarahdean011

Recap

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

Agenda

 

0. Recap & Announcements

1. Markov Decision Process

2. Value and Q functions

3. Policy Evaluation

4. Approximate Policy Evaluation

5. State-Action Distribution