COMP 552: REINFORCEMENT LEARNING
Fall 2024 · Section 001 · CRN 15017
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
- Credits
- 3
- Instructors
- Vaibhav Unhelkar