@article{Lian_Mattei_Noble_Walsh_2018, title={The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods}, volume={32}, url={https://ojs.aaai.org/index.php/AAAI/article/view/11484}, DOI={10.1609/aaai.v32i1.11484}, abstractNote={ <p> 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 SUM-OWA assignment in polynomial time, in contrast to the NP-hardness of finding an egalitarian assignment. We demonstrate through empirical experiments that using SUM-OWA assignments can lead to high quality and more fair assignments. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Lian, Jing Wu and Mattei, Nicholas and Noble, Renee and Walsh, Toby}, year={2018}, month={Apr.} }