This report is a summary of my work under the guidance of Dr. Mark Jakiela during the Spring 2020 semester. I have worked with Dr. Jakiela on this independent study project which complements his research interests in computer-supported collaborative work (“CSCW”) systems. These can be applied to higher-level, more complex tasks. This independent study examines contribution attribution via fair division. The goal of this project is to develop a program to decide whether a member in a team-based project group could receive a reward or not, based upon their contribution. I came up with the idea to use a perception learning algorithm to develop a program for this application. The report consists of four parts. The first two parts illustrate the significance of this project and why machine learning can be applied. The third and fourth parts describe how the program is developed and tested, along with an analysis of the results.
Mechanical Engineering and Material Sciences Independent Study
Date of Submission
Lu, Kuan, "MEMS 500 Independent Study Report: Contribution Attribution via Fair Division" (2020). Mechanical Engineering and Materials Science Independent Study. 125.