Syllabus
Administrative Information
The syllabus information is seen below. This is a PDF copy of the syllabus .
Lecture Information
Lectures are Tuesday and Thursday, 11:30 am - 12:45 pm, MSC W301
Staff and Office Hours
Office Hours will be decided after the first week of class
Catalog Information
3 credits. General Education Requirement for First-year students. No Prerequisites. Not cross listed. Topics will be announced each semester when class is scheduled.
Prerequisites
Assumed some knowledge of calculus, matrices, and basic probability. This will be reviewed the first week of classes. Anything harder than the basics will be computed via MATLAB, which will also be taught.
Texts
Recommended Texts
- Game Theory: An Introduction (GT), by Steven Tadelis
- Elementary Linear Programming with Applications (LP), by Kolam, Beck
- Essentials of Stochastic Processes (SP), by Rick Durrett
While this looks like a lot of reading and spending money on book, the course team has considered this. We are only going to cover GT Chap 1-3 (selected topics), LP Chap 1, and SP Chap 1. Also, all of the books are freely available online (at the links above).
References
Course Work
Homework
You will have two homeworks per module and one homework at the beginning to set expectations of the material. There will be 7 total homework assignments. The assignments will be posted on and submitted through Canvas. The homework will be due on Tuesday at 11:30 am, which is the beginning of class, (except for holidays) and will be posted no later than three classes beforehand (Thursday the week prior). The number of questions may vary week to week, but the assignments will not be very long. You will upload your written homework to Canvas in PDF format to grade.
The lowest two homework grades will be dropped. No makeup assignments will be given. If you have to miss an assignment, it will be one that is dropped.
Homework assignments will be graded on an individual basis. The instructor allows discussions with other students while solving the problems. The only requirement is that you acknowledge all contributors and sources used. Yes, this does include large language models such as ChatGPT. Identical solutions that are seen as Honors Code violations, will not be graded and will be reported to the Honor Council. The border between acceptable and unacceptable collaboration may be subtle. If you are uncertain whether a particular behavior is acceptable or not, please ask the instructor or teaching assistant as soon as possible.
Projects
There will be 3 module projects, which will be a combination of individual and small group projects. There will be a written and oral portion of each project. No project is dropped, and each are weighted equally, i.e. each project is 20% of your final course grade.
These projects allow us the flexibility to apply the mathematical topics from class in the broader context of environmentalism, sustainability, and green business.
There will be some class time dedicated to each project, but most work will have to be done outside of class time.
Exams
There will be one midterm exam given in class, on Nov. 7. You will be given the full class period (75 minutes) to take the midterm.
The final exam will be a final presentation to your Module 3 project. It will take place during finals week on Monday, Dec. 17, from 11:30 AM to 2:00 PM.
Conflicts with the final exam time slot must be reported through the Office for Undergraduate Education (OUE). You must notify the instructor at least two weeks before the exam date if you have a conflict, or have a valid excuse verified by the Office of Undergraduate Education (OUE).
Grading
Schedule
This schedule is tentative and subject to change.
| Week | Date | Topics | Homework |
|---|---|---|---|
| 1 | R 8-29 | Syllabus, Matrix Review | |
| 2 | T 9-3 | Matrix Review | |
| R 9-5 | Single Person Games | ||
| 3 | T 9-10 | Decision Trees | HW0 Due |
| R 9-12 | Static Games | ||
| 4 | T 9-17 | Strategy Types | |
| R 9-19 | Nash Equilibria | ||
| 5 | T 9-24 | Dynamic Games | HW1 Due |
| R 9-26 | Incomplete information | ||
| 6 | T 10-1 | Game Theory Presentations | |
| R 10-3 | Linear Programming | ||
| 7 | T 10-8 | Matrix Notation of Linear Programming | HW2 Due |
| R 10-10 | Geometry of Linear Programming I | ||
| 8 | T 10-15 | Fall Break (no class) | |
| R 10-17 | Geometry of Linear Programming II | ||
| 9 | T 10-22 | Linear Programming 4 | HW3 Due |
| R 10-24 | Linear Programming 4 | ||
| 10 | T 10-29 | Project Work Day | |
| R 10-31 | Chocolate Presentations | ||
| 11 | T 11-5 | Midterm Review | HW4 Due |
| R 11-7 | Midterm Exam | ||
| 12 | T 11-12 | Introduction to Markov Chains | |
| R 11-14 | Multistep Transitions | ||
| 13 | T 11-19 | State Classification | |
| R 11-21 | Stationary Distributions | ||
| 14 | T 11-26 | Limit Behavior | HW5 Due |
| R 11-28 | Thanksgiving Break (no class) | ||
| 15 | T 12-3 | Special Examples | |
| R 12-5 | Catch-up | ||
| 16 | T 12-10 | Catch-up | HW6 Due |
| Finals | T 12-17 | 11:30am - 02:00pm, MSC - N301 |