from

Offered through the University of Maryland

CMSC389F: Reinforcement Learning is a University of Maryland course that I will be teaching in the Spring of 2018. The course website can be found here.

The course provides a theory-centric introduction to Reinforcement Learning. Students will learn the key concepts and algorithms driving Reinforcement Learning, including Markov Decision Processes, Monte Carlo Learning, and Policy Gradient methods. The course will culminate in a final reinforcement-learning project built on OpenAI Gym that will be presented to the class.

The subject is taught to University of Maryland upper-level undergraduate students. Details for the class are here.


← CMSC651: Advanced Algorithms | Class Archive | PHIL209N: Wisdom Through Cognitive Science →

about

I’m Kevin Chen, and this is my personal website. I am a rising final-year student in the CS department at the University of Maryland. ¶ My research interests are in machine learning and theoretical computer science. I enjoy reading, filmmaking, tennis and helping out with Bitcamp.

subscribe

To receive updates from this site, you can subscribe to the  RSS feed of all updates to the site in an RSS feed reader.

search