Computer Science · Fall 2026
SDSU CS 654 — Reinforcement Learning
Reinforcement Learning studies sequential decision-making to maximize cumulative rewards. Widely applied in robotics, finance, healthcare, etc., this course covers topics like Markov decision processes, value-based RL, actor-critic methods, policy gradients, and imitation learning, with practical projects.
Course requirements
Prerequisites: CS 549, graduate standing, or consent of the instructor.
- CS 549, graduate standing, or consent of the instructor.
Fall 2026 enrollment options
Seat status can change| Class # | Format | Status | Seats | Time | Location | Professor | RateMyProfessors |
|---|---|---|---|---|---|---|---|
| 10053 Lecture | In person | Open | 56 / 60 | Tue/Thu 7:00 PM–8:15 PM | P 146 | Xin Zhang | No RateMyProfessor match available |