Policies

Waitlist and PTA Numbers

Historically there has been a waitlist for this class. If you are on the waitlist, please see my guide on PTA numbers here: here

Meetings

• 30 Lectures, 50 minutes each, MWF
• 10 Discussions, 50 minutes each, T

Course Topics:

• Knowledge representation and reasoning
• Theory and advanced programming techniques
• Topics selected from areas of expert systems, natural language processing, image understanding, machine learning, games, and robotics

Course Staff

Name	Role	Email	Office Hours
Gabriel Simmons	Instructor	gsimmons@ucdavis.edu	Fridays 3-4pm (in-person, Kemper 3052)
Dongwon Jung	TA	dwojung@ucdavis.edu	Wednesdays 3-4pm (Zoom)
Vincent Huynh	TA	vvhuynh@ucdavis.edu	Tuesdays 2-3pm (in-person, Kemper 55)

Prerequisites

Pre-requisites: ECS 060 or ECS 032B or ECS 036C

Communication Policy

Please use email to communicate with course staff. Course staff will not respond to messages submitted via the Canvas messaging system.

Emails MUST include the course code in the subject line. Please. We're begging you.

More tips for emails:

1. Use a descriptive subject line.
2. If you are asking for something, make it clear in the first 1-2 sentences.
3. If you use ChatGPT or other email generators, use a prompt that encourages very succinct, direct emails. The default behavior of these tools is to generate long, rambling emails. I am much more likely to respond to a short, direct email with a clear ask.
4. Don't use email for questions that will take more than a paragraph of writing to conclude, either from yourself or from the course staff. Please use the Instructor and TA office hours for these sorts of open-ended discussions.

If you resolve your issue on your own, please send a follow-up in the same email thread (reply all to yourself and the course staff that you sent the email to). This can be as simple as "This issue is resolved, no help needed." If you have more time, feel free to share how you resolved your email. Other students may be struggling with the same thing, and the course staff may share your feedback with them.

Who to contact, and how:

Please use Piazza for:

• Questions about lecture content or other course material
• Questions about course logistics that are relevant to the whole class

Please come to office hours for:

• Detailed feedback on project ideas
• Help with homework or course project

Please email the course instructor for:

• Personal issues that require accomodations for more than one assignment,
• Requests for Incomplete (I) grade

Please email the TAs and cc the course instructor for:

• Setting up a time to take a remote or in-person make-up quiz
• Resolving grading issues

If you're unsure:

• Email the TAs

Auditing

In most cases, I am happy to have folks audit the class.

Send me an email with subject line `ECSXYZ request to audit`, replacing ECSXYZ with the real course code.

Please note the following:

1. I generally recommend that auditors do not participate in group work. If you really want to participate in group work, please ask. I will ask you to commit to giving the same level of effort that you would as a graded student.

2. Your individual work will probably not be graded, or may be graded at a lower priority than work from registered students. You are welcome to assess yourself based on any posted assignment solutions, rubrics, etc.

   For each of the following 4 assignments:

   • Project Proposal

   • Project Check-in

   • Project Presentation

     Create corresponding Peer Feedback 1 and Peer Feedback 2 assignments (6 peer feedback assignments in total)

Attendance

• Attendance is expected in-person, including all discussion sections
• We will try to provide video recordings of lectures and discussions and make them available on Canvas. This depends in part on the video recording facilities available in our assigned lecture and discussion rooms.

Grading

The table below indicates the grading policy for the course. There will be several in-person quizzes taken during discussion. The lowest (1) quiz grade will be dropped. In-person attendance at the final will be required. Please check Schedule Builder for the final exam date and time.

Students will be required to complete a group project implementing, evaluating, or critiquing an AI algorithm, dataset, or other AI-related artifact. Students will write a written report and present their work. Students may optionally produce a web application demonstrating their final project.

There will be weekly perspective readings on topics related to the history, philosophy, and technical details of artificial intelligence and related fields. Students will submit reading reflections for each week's assigned readings.

There will be 1-4 individual homework assignments requiring students to implement AI algorithms presented during lectures.

Assignment Category	Grade Percentage
Project Group Signup	1
Project Proposal	2
Project Check-In	3
Collaboration Survey 1	0.5
Peer Feedbacks	3
Project Presentation	15
Project Report and Code	15
Collaboration Survey 2	0.5
Quizzes (6), equally weighted	30
Homeworks (2-4), equally weighted	20
Reflections (10), equally weighted	10
Total	100.

Regrade Requests

The availability of regrades is on a per-assignment basis. If regrades are available for an assignment, the last day to submit a regrade request is 1 week after the assignment deadline, or the last day of instruction (typically the Friday before finals week), whichever is earlier.

Materials

1. Textbook

   Artificial Intelligence: A Modern Approach - Stuart Russell and Peter Norvig - 3rd Edition

2. Other Readings

   Other selected readings for the course will be posted on Canvas. Readings from past versions of the course have included essays and book excerpts from:

   • Melanie Mitchell (Artificial Intelligence)
   • Brian Christian (The Alignment Problem)
   • Stuart Russell
   • Alan Turing
   • Dan Hendrycks
   • Richard Sutton
   • and many more…

3. Canvas

   Please make sure that you are added to this course on Canvas. Check Canvas for ECS 170 regularly. Announcements on important information about the course, including course assignments, will be made on Canvas.

4. Piazza

   Please sign up for this course on Piazza. Check the Canvas announcements for signup instructions.

5. Gradescope

   All assignments will be submitted through Gradescope. The course Gradescope can be accessed at: https://www.gradescope.com/courses/1141022

   • Homework assignments, project components, and reading reflections will all be submitted via Gradescope
   • Make sure you are enrolled in the course on Gradescope
   • Most writing submissions will be in PDF or Markdown format

6. Python

Use of the Python programming language will be encouraged (potentially required) for the programming assignments for this course. If you have not programmed in Python before, I would encourage you to explore the langauge via some tutorials. Ask around in class to find a knowledgeable friend.

Extra Resources

• CS188 Lecture Series, UC Berkeley
• How AI Can Prevent Blackouts

Assignments

All assignments should be submitted through Gradescope: https://www.gradescope.com/courses/1141022

Title	Deadline
Group Formation	2025-10-03T06:59:00Z
Reflection 1	2025-10-03T06:59:00Z
Project Proposal	2025-10-10T06:59:00Z
Reflection 2	2025-10-10T06:59:00Z
Homework 1	2025-10-17T06:59:00Z
Reflection 3	2025-10-17T06:59:00Z
Reflection 4	2025-10-24T06:59:00Z
Reflection 5	2025-10-31T06:59:00Z
Reflection 6	2025-11-07T06:59:00Z
Project Check-In	2025-11-12T06:59:00Z
Collaboration Survey 1	2025-11-12T06:59:00Z
Reflection 7	2025-11-14T06:59:00Z
Homework 2	2025-11-19T06:59:00Z
Reflection 8	2025-11-21T06:59:00Z
Reflection 9	2025-12-03T06:59:00Z
Collaboration Survey 2	2025-12-05T06:59:00Z
Reflection 10	2025-12-05T06:59:00Z
Project Report & Code	2025-12-09T06:59:00Z

Late Work

• Homeworks: Late work will be accepted with a linear penalty up to 1 week after the assignment deadline for Homeworks.
• Project: Late submissions will not be accepted for assignments related to the course project
• Reflections: Late submissions will be accepted with a linear penatly up to 1 week after the assignment deadline for Reflections.

Late Assignment Scoring

When an assignment is submitted late, the final score is calculated by first grading the assignment normally, then applying a late penalty that increases linearly over time, up to one week late.

Formula

For an assignment submitted d days late (where 0 ≤ d ≤ 7):

$$\text{Final Score} = \text{Original Score} \times (1 - \frac{d}{7})$$

Examples

• If you score 90% on the assignment and submit 1 day late:
  • Final Score = 90% × (1 - 1/7) = 77.1%
• If you score 80% on the assignment and submit 3 days late:
  • Final Score = 80% × (1 - 3/7) = 45.7%
• If you submit more than 7 days late:
  • Final Score = 0% (regardless of original score)

Note: Partial days are counted proportionally. For example, submitting 12 hours late would count as 0.5 days (d = 0.5).

Assignment Late Penalty

SDC Accomodations

Sufficient notice is needed in order to make the accommodations possible. If you need disability-related accommodations in this class, please email sdc@ucdavis.edu or call them at (530) 752-3184. The student disability center is the campus office responsible for verifying that students have disability-related needs for academic accommodations, and for planning appropriate accommodations in cooperation with the students themselves and their instructors.

Academic Honesty

Students are expected to follow the UC Davis Code of Academic Conduct. See: https://ossja.ucdavis.edu/code-academic-conduct

Note on Discrimination, Harassment, and Retaliation (DHR)

The University of California and UC Davis Health are committed to the principle of treating each community member with respect and dignity. Across all of its locations, including clinical settings, the University prohibits discrimination and harassment (including sexual assault and other forms of sexual harassment). For more on the University's commitment to integrity, accountability and respect for all members of our community, please see the University's Statement of Ethical Values and Standards of Ethical Conduct at: https://www.ucop.edu/ethics-compliance-audit-services/index.html. See also: https://compliance.ucdavis.edu/compliance-program and https://hdapp.ucdavis.edu/non-discrimination-statement

University Holidays

See the below URL to know about the University and National Holidays: https://registrar.ucdavis.edu/calendar/web/holidays

Policy on Add, Drop and Withdrawal

Please look at the below URL to know about the add, drop and withdrawal dates: https://registrar.ucdavis.edu/registration/register-for-classes/schedule-adjustments/add-drop

Academic Calendar

Important dates are listed in the UC Davis Academic calendar: https://www.ucdavis.edu/campus-life/things-to-do/calendar/academic