Policies

Meeting Times

Mondays and Wednesdays 9:40-11:10 in 407 S. Craig St.

Instructors

Stephanie Rosenthal (srosenth@andrew), office hours held on Zoom

• Office Hours: Tuesdays 10:30-12pm, Wednesdays 12-1:30pm, or by appointment

Reid Simmons (rsimmons@andrew), office hours held on Zoom

• Office Hours: Mondays 2-3pm, Thursdays 4-5pm, or by appointment

Learning Objectives

• Design and implement algorithms for single agent architectures, finite state machines, error monitoring and testing, explanation of agent behavior, computer vision, optimization and machine learning, resource optimization, scheduling, and task planning.
• Apply AI decision-making techniques to novel environments and scenarios
• Evaluate and explain the tradeoffs in implementing and deploying different AI algorithms to solve a problem
• Design and develop an autonomous agent and test it in simulation and in the real world
• Analyze the performance of a deployed agent in simulation and the real world
• Discuss the ethical considerations to be made while implementing and deploying autonomous agents

Textbooks

We encourage the use of the textbook Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig.

Assignments

Students will work individually to practice weekly themes taught in class. Additionally, students will work in groups of 3 to use their skills from the individual assignments to implement an autonomous greenhouse agent. The agent will be built up through three group assignments and deployed on our greenhouse architecture once a month. After every grow period, students will write up and present a description of the algorithms used, lessons learned, and an evaluation of the deployed agent. In addition to deployments, each of the assignments will be evaluated using a greenhouse simulator with instructor-determined test conditions and student-generated tests. Assignment grades will be a combination of the simulator evaluations, the growing cycle, and the write-up and presentation, when applicable. The exact rubric to be used will be provided for each assignment.

Grading

In addition to the individual assignments and project, there will be a midterm, a final exam, and peer evaluations of group participation. Grades will be collected and reported in Canvas. The final grade will be calculated as follows:

• 30% Individual Assignments (5% each):
  • Assignment Code (3% x 6)
  • Tests (2% x 6)
• 30% Group Assignments (10% each):
  • Project code (7% x 3 assignments)
  • Thorough tests (3% x 3 assignments)
• 10% Grow Period Deployments (5% each)
  • Grow period execution (2.5% x 2)
  • Grow period presentations/writeups (2.5% x 2)
• 10% Midterm
• 15% Final Exam
• 5% Peer Evaluation

Collaboration Policy

Collaboration Policy We encourage you to discuss course content and the project with all of your classmates. However, these discussions must be kept at a conceptual level only for individual assignments. You may share information from other teams about the algorithms or code packages that are being used, but may NOT directly copy code implementation or text. You may also look at another student's Python error messages and discuss what the error means to help them solve it.

Individual Assignment Late Policy

Assignments are due at noon on Wednesday. Assignment submission instructions will be provided on a per-assignment basis. Students are given 3 grace days to use throughout the semester on any combinations of assignments (all three on one assignment, 2 on one and 1 on another, etc). If you run out of grace days, a 10% deduction in code-related points will be applied.

Group Assignment Late Policy

For the group assignment submissions leading up to the Grow Periods, the professors will upload the submitted code to the greenhouses and start running them on Thursday at noon. An additional 2 grace days will be available for group assignments. These grace days are used as a team.

Grow Period Restart Policy

Our code will monitor the health of your agent and if it hangs or crashes, our program will restart it at no penalty. If it crashes too frequently, you will receive an email. If you wish to give us new code to run, we will manually upload it and restart your agent at a 10% penalty per upload.

Extensions

We understand that emergencies and unexpected events happen. Please let the instructors know as soon as possible if you have questions about extensions.

Plagarism

Cheating—and plagiarism specifically—is a very serious violation of both academic integrity and CMU policy. All content produced for this class must be original to the submitter unless otherwise stated. Plagiarism is a very serious offense, and will be treated as such. Any sources of information should be cited and acknowledged – if you get assistance from other students or CMU academic resources, you should acknowledge that assistance in the write-up to your assignment (who helped and in what way). It is not a problem for someone to give you general assistance about the techniques used in assignments; it is a problem if they help provide solutions to the specific assignment. Do not take chances with plagiarism: if you are uncertain whether you are doing something acceptable, please just ask. We are happy to answer questions about whether something constitutes plagiarism.

Acommodations

If you have a disability and have an accommodations letter from the Disability Resources office, we encourage you to discuss your accommodations and needs with us as early in the semester as possible. We will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, then we encourage you to contact them at access@andrew.cmu.edu.

Health and Wellness

Do your best to maintain a healthy lifestyle this semester by eating well, exercising, avoiding drugs and alcohol, getting enough sleep and taking some time to relax. This will help you achieve your goals and cope with stress. All of us benefit from support during times of struggle. If you or anyone you know experiences any academic stress, difficult life events, or feelings of anxiety or depression, we strongly encourage you to seek support. Contact the Counseling and Psychological Services (CaPS) office at 412-268-2922 and visit their website at http://www.cmu.edu/counseling for more information.

If you or someone you know is in danger of self-harm, please call someone immediately, day or night:
CaPS: 412-268-2922
Re:solve Crisis Network: 888-796-8226
CMU Police: On-Campus 412-268-2323, Off-Campus 911