CS 175: Project in Artificial Intelligence

Winter 2026

Schedule

Note: the planned schedule is subject to change. Course materials will regularly be added above.

Course logistics

• When: Wednesdays at 6:30–9:20pm, only in weeks 1, 2, and 5. No discussion section.
• Where: ICS 174.
• Format:
  • Team and individual project work:
    • This is the main activity in this course. Please start early and meet often.
    • Project teams are responsible for making steady progress and scheduling meetings among themselves and with course staff.
  • Lectures:
    • In weeks 1 and 2, we will introduce reinforcement learning, suggested project platforms, and the course expectations and evaluation criteria.
    • In week 5, we will meet to share experience across teams and discuss common issues.
    • These lectures will be in-person and their records will be posted above.
    • Lecture attendance is optional but an exact online replica of the in-person materials cannot be guaranteed.
  • Project meetings:
    • Each team will meet the instructor periodically.
    • In-person and virtual meeting slots will be posted throughout the quarter.
    • The minimum requirement is for three meetings with the instructor, by the end of weeks 3, 6, and 9.
    • More than the minimum frequency of meetings is strongly encouraged.
  • Exercises:
    • To get you started, 2 exercises will be due on weeks 3 and 4.
  • Reports:
    • Project proposals and reports will be due on weeks 3, 7, and 10.
  • Presentations:
    • In week 10, the class will meet again for teams to present their projects.
  • There will be no discussion section meetings. There will be no exams.
• Ed Discussion:
  • Please use the forum for course-related discussions.
  • Important course announcements will be posted there as well (not on Canvas).
  • Please use the forum (not email) to privately message course staff about course-related matters.
  • Please note that the identity of anonymous posters is visible to the course staff.
• Canvas:
  • Instructions for exercises, proposals, and reports will be posted above and their submission will be on Canvas.
  • Canvas will also be used to manage teams and report grades.
• Instructor: Prof. Roy Fox
  • Office hours: in-person or on zoom.
  • When scheduling a project meeting, please make sure to invite all your teammates.
  • More times available by request.
• Teaching assistants:
  • Yuchen Song (lead TA), office hours
  • Kyungmin Kim, office hours

Grading policy

• Exercises: 10% (individual)
  • Late submission: 3 grace days total, for both assignments, per person
• Project proposal: 10% (team)
• Progress report: 20% (team)
• Final report: 40% (team + individual component)
  • Late submission: 5 grace days total, for all project submissions, per team
• Project presentation: 15% (team)
• Participation (meetings, forum, evaluations): 5% (individual)
• No exams

Resources

Past projects

Compute Resources

• HPC3
• ICS Openlab

RL tutorials

• Basic tutorial and worked examples
• Blog series providing gentle intro
• Intro to DeepRL algorithms

RL libraries

• Stable Baselines3
• RLlib
• MushroomRL
• Coach

Courses

• Roy Fox (UCI)
• Sergey Levine (Berkeley)
• David Silver (UCL)
• Dimitri Bertsekas (MIT)

Books

• Richard Sutton & Andrew Barto
• Vincent François-Lavet et al.
• Csaba Szepesvári