Course Schedule and Catalog
Course Schedule - Fall Semester 2025
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
COMP 552 001 (CRN: 12910)
REINFORCEMENT LEARNING
Long Title: REINFORCEMENT LEARNING
Department: Computer Science
Instructor: Unhelkar, Vaibhav
Meeting: 4:00PM - 5:15PM TR (25-AUG-2025 - 5-DEC-2025)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 80
Section Enrolled: 51
Total Cross-list Max Enrollment: 80
Total Cross-list Enrolled: 84
Waitlisted: 24 (Max 198)
Current members of the waitlist have priority for available seats.
Enrollment data as of: 19-APR-2025 11:23PM
Final Exam: GR Course-Dept Schedules Exam
Description: This course introduces students to reinforcement learning (RL), a general and impactful machine learning paradigm for solving sequential decision-making problems and designing autonomous agents. The course will cover both classical and recent algorithms for reinforcement learning (including deep RL) and imitation learning (including inverse RL). Through the assignments and final project, students will get hands-on experience in applying reinforcement learning algorithms to solve problems inspired by real-world applications. The course will conclude with an overview of open problems and ongoing research in reinforcement learning. Cross-list: COMP 442. Recommended Prerequisite(s): COMP 330 or COMP 440 or ELEC 478 or COMP 540