Host: The Japanese Society for Artificial Intelligence
Name : The 38th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 38
Location : [in Japanese]
Date : May 28, 2024 - May 31, 2024
The theory of two-sided matching has been extensively developed, and it is hoped that matching will reduce students' envies and improve overall welfare. However, it turns out that there exists a trade-off between efficiency and fairness. Therefore, keeping fairness at a certain level that can be applied in the real world also leads to increased efficiency. Our contribution is to establish a weaker fairness requirement called reverse Envy-Freeness from up to k peers (r-EF-k). r-EF-k requires that each student is envied by at most k students. By varying k, r-EF-k can represent different levels of fairness. We discuss mechanism that satisfy r-EF-k and certain efficiency properties.
