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Course number: CSE 190 - Deep Reinforcement Learning

Course Description

This course will cover the basics of (1) what LLM-based AI Agents actually are; (2) where they can be useful (and where they are not); and (3) how to safely train and deploy an agent for a given virtual domain.

Rough Outline

Required Knowledge

Students should be familiar with basic CS concepts such as Search (BFS/DFS/A*). Students are expected to come into the class with the ability to implement these concepts from scratch (in Python/numpy) and also be able to use popular libraries such as Huggingface. Basic knowledge of Machine / Reinforcement / Deep Learning is a plus but is not required.

Undergrad Intro to AI/RL, and grad level Intro to Deep Learning / NLP types of courses are highly recommended

Website pearls-lab.github.io/intro-deep-rl-course

Instructors: Prithviraj Ammanabrolu

TAs: Bosung Kim

Time and Place

Office Hours (see the Staff page for office hour locations)

Course Materials

There is no textbook for this course, but you will be required to puchase a varitey of materials including software and API credits. If any of these are prohibitively expensive for your budget, please let the instructor know.

Grading

Collaboration Policy

Homeworks are expected to be done individually.

LLM Use Policy

You may use LLMs for code completion on coding assignments but must submit a CREDITS.txt file noting the exact LLM you used along with prompt. All homeworks will also require explanations written of the code which must be done solely without an LLM. Writing on final projects can be edited but not entirely written with an LLM. Failure to comply with any of these policies will result in a 0 on that particular assignment.

Late Day Policy

Each student has five free “late days”. Homeworks can be submitted at most two days late. If you are out of late days, then you will not be able to get credit for subsequent late assignments. One “day” is defined as anytime between 1 second and 24 hours after the homework deadline. The intent of the late day policy it to allow you to take extra time due to unforseen circumstances like illnesses or family emergencies, and for forseeable interruptions like on campus interviewing and religious holidays. You do not need to ask permission to use your late days. No additional late days are granted. Late days only apply to the homeworks. They cannot be used on the final project, which must be finished by the final day of class. Late days may not be used for project presentations.