Mondays and Wednesdays 12:00-1:20 in GHC 4102
Stephanie Rosenthal (srosenth@andrew), GHC 6019
- Tuesdays 2:30-4pm, Wednesdays 9-10:30am, or by appointment
Reid Simmons (rsimmons@andrew), NSH 3213
- Mondays 2-3pm, Thursdays 4-5pm, or by appointment
15-281 or 15-381 or 10-301 or 10-315 or permission by instructors.
We encourage the use of the textbook Artificial Intelligence: A Modern Approach
by Stuart Russell and Peter Norvig.
Students will work in groups to implement an autonomous greenhouse agent. The agent will be built
up through six assignments and deployed on our greenhouse architecture once a month.
Students will submit write-ups about their algorithm choices and implementation to be graded in simulation and through a real world deployment.
Deployments will also include a graded presentation and written report evaluating the deployment of the agent after the grow periods. Assignments will be submitted following the instructions on Canvas.
Students will work in groups of 3 to implement an autonomous greenhouse agent using AI-based techniques. The agent will be built up through six assignments and deployed on actual greenhouse hardware, with sensors and actuators, once a month. In addition, each of the assignments will be evaluated using a greenhouse simulator with instructor-determined test conditions.
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. All assignments will be submitted following the instructions on Canvas.
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.
We encourage you to discuss course content and the project with all of your classmates. However, these discussion must be kept at a conceptual level only. 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.
There will be six bi-weekly group project assignments that apply lecture concepts to an autonomous
greenhouse application that will be graded in simulation for completeness and robustness.
After every other assignment, we will deploy the agents to autonomously grow plants for two weeks.
Grow periods will be graded based on a combination of metrics including how many times the teams manually
restarted or updated their code, the plant growth and health, and resource usage.
After each grow period, each group will be asked to present their approach and results to the
class and write up their results in a report as part of the project grades.
In addition to the project, there will be two midterms, a final exam, and peer evaluations of
Grades will be collected and reported in Canvas. The final grade will be calculated as follows:
- 60% Project Assignments:
- Project code 30% (5% x 6 assignments)
- Grow period presentations/writeups 15% (5% x 3 periods)
- Grow period deployment 15% (5% x 3 periods)
- 20% Midterms (10% each)
- 15% Final Exam
- 5% Peer Evaluation
Assignments are due at noon on Wednesday. The professors will upload the submitted code to the greenhouses and start running them on Thursday at noon. 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). The late days are used as a team. If you run out of grace days, a 10% deduction in simulator-graded points will be applied.
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.
We understand that emergencies and unexpected events happen. Please let the instructors know as soon as
possible if you have questions about extensions.
Cheating—and plagiarism specifically—is a very serious violation of both academic integrity and
. 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.
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 email@example.com.
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:
Re:solve Crisis Network: 888-796-8226
CMU Police: On-Campus 412-268-2323, Off-Campus 911