Introduction to Reinforcement Learning
ECE 433/COS 435
1244
1244
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Reinforcement learning (RL) is a core technology at the heart of modern AI about using machine learning and AI methods to make decisions that lead to good outcomes. In this course, we aim to give an introductory overview of reinforcement learning, fundamentals concepts and algorithms, as well as core challenges in RL including exploration and generalization. The course will also highlight case studies of RL applications to real-world problems, including health care and molecular science. Assignments for this lecture-based course will include written mathematical exercises, implementing RL algorithms, as well as a final group project.
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Section L01
- Type: Lecture
- Section: L01
- Status: O
- Enrollment: 72
- Capacity: 88
- Class Number: 41179
- Schedule: TTh 11:00 AM-12:20 PM - Thomas Laboratory 003
Section P01
- Type: Precept
- Section: P01
- Status: O
- Enrollment: 24
- Capacity: 40
- Class Number: 42731
- Schedule: Th 01:30 PM-02:20 PM - Friend Center 006
Section P02
- Type: Precept
- Section: P02
- Status: C
- Enrollment: 0
- Capacity: 0
- Class Number: 42732
- Schedule: Th 02:30 PM-03:20 PM
Section P03
- Type: Precept
- Section: P03
- Status: O
- Enrollment: 27
- Capacity: 40
- Class Number: 42733
- Schedule: F 11:00 AM-11:50 AM - Friend Center 006
Section P04
- Type: Precept
- Section: P04
- Status: O
- Enrollment: 21
- Capacity: 40
- Class Number: 42975
- Schedule: Th 03:30 PM-04:20 PM - Sherrerd Hall 101