CSC 395-02 - Special Topic: Introduction to Reinforcement Learning (RL) and Multi-Agent Systems (MAS)

4 credits (Spring)

This is an introductory but in-depth study of reinforcement learning (RL) techniques and multiple applications. This course is divided into two parts. Part I focuses on the origins (psychology), foundations and traditional RL algorithms. Part II focuses on different applications of RL, such as: multi-agent tasks, robotic tasks, bio-inspired computational approaches, and deep learning. Another aspect of this course is to help students develop scientific skills. At the end of this course, students will be able to develop RL algorithms, use a proper machine learning terminology, and generate data graphics to discuss and analyze learning challenges driven by self-centered decision-making.

Prerequisite: CSC 161 and CSC 208, MAT 208, or MAT 218.
Note: Plus-2 option available.
Instructor: Eliott