Gaurav Goswami, Nalini K. Ratha, et al.
AAAI 2018
We propose a novel mechanism for solving the assignment problem when we have a two sided matching problem with preferences from one side (the agents/reviewers) over the other side (the objects/papers) and both sides have capacity constraints. The assignment problem is a fundamental in both computer science and economics with application in many areas including task and resource allocation. Drawing inspiration from work in multi-criteria decision making and social choice theory we use order weighted averages (OWAs), a parameterized class of mean aggregators, to propose a novel and flexible class of algorithms for the assignment problem. We show an algorithm for finding an Σ-OWA assignment in polynomial time, in contrast to the NP-hardness of finding an egalitarian assignment. We demonstrate through empirical experiments that using Σ-OWA assignments can lead to high quality and more fair assignments.
Gaurav Goswami, Nalini K. Ratha, et al.
AAAI 2018
Cristina Cornelio, Judy Goldsmith, et al.
JAIR
Harshit Kumar, Arvind Agarwal, et al.
AAAI 2018
Senthil Mani, Neelamadhav Gantayat, et al.
AAAI 2018