Majoritarian Assignment Rules
For researchers in multiagent systems and social choice, this work provides a novel theoretical framework for analyzing assignments using majority graphs, with surprising structural results.
This paper introduces majoritarian social choice functions to the assignment problem, showing a near one-to-one correspondence between preference profiles and majority graphs, which allows key properties like Pareto-optimality and popularity to be determined solely from the graph. The main result fully characterizes the top cycle, showing it can only consist of one, two, all but two, all but one, or all assignments.
A central problem in multiagent systems is the fair assignment of objects to agents. In this paper, we initiate the analysis of classic majoritarian social choice functions in assignment. Exploiting the special structure of the assignment domain, we show a number of surprising results with no counterparts in general social choice. In particular, we establish a near one-to-one correspondence between preference profiles and majority graphs. This correspondence implies that key properties of assignments -- such as Pareto-optimality, least unpopularity, and mixed popularity -- can be determined solely by the associated majority graph. We further show that all Pareto-optimal assignments are semi-popular and belong to the top cycle. Elements of the top cycle can thus easily be found via serial dictatorships. Our main result is a complete characterization of the top cycle, which implies the top cycle can only consist of one, two, all but two, all but one, or all assignments. By contrast, we find that the uncovered set contains only very few assignments.