CS 751 (01) - Reinforcement Learning

Reinforcement Learning

Durham Engineering&Physical Sciences::Computer Science
Credits: 4.0
Class Size: 50 
Term:  Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
CRN:  16260
Grade Mode:  Letter Grading
Reinforcement learning studies how agents can learn to act to achieve goals in complex, stochastic environments. This course introduces students to fundamental theoretical concepts of reinforcement learning, standard algorithms, and practical techniques. In addition to theoretical topics, the course involves implementing basic algorithms in a high-level programming language.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Cross Listed With : CS 851A (01)
Prerequisite(s): (CS 415 or CS 410P) and (MATH 539 or MATH 644)
Instructors:  Marek Petrik

Times & Locations

Start Date End Date Days Time Location
8/26/2024 12/9/2024 TR 9:40am - 11:00am KING N101
Final Exam12/11/2024 12/11/2024 W 10:30am - 12:30pm KING N101