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

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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