EE 4190 - Reinforcement Learning and Neural Networks in Intelligent Control

Credit Hour(s): 3

Course Description: Introduction to reinforcement learning and neural networks for intelligent control. Inspired by neuroscience and bio-inspired machine learning, combines deep neural networks with a reinforcement learning architecture that enables intelligent agents to learn from their actions similar to the way humans learn from experience. Emphasis on conceptual understanding of deep reinforcement learning algorithms and their applications to practical design or intelligent control systems.

Prerequisite(s): Undergraduate level MTH 2350 Minimum Grade of D

Corequisite(s): EE4190L

Enrollment Restrictions: Must be enrolled in one of the following colleges: College of Egr & Computer Sci.

Course Level: Undergraduate
Schedule Type(s): Lecture

Grade Mode: Standard
An additional fee is associated with this course.