TY - GEN
T1 - Parameterized Analysis of Assignment Under Multiple Preferences
AU - Steindl, Barak
AU - Zehavi, Meirav
N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.
PY - 2021/7/20
Y1 - 2021/7/20
N2 - The Assignment problem is a fundamental and well-studied problem in the intersection of Social Choice, Computational Economics and Discrete Allocation. In the Assignment problem, a group of agents expresses preferences over a set of items, and the task is to find a pareto optimal allocation of items to agents. We introduce a generalized version of this problem, where each agent is equipped with multiple incomplete preference lists: each list (called a layer) is a ranking of items in a possibly different way according to a different criterion. We introduce the concept of global optimality, which extends the notion of pareto optimality to the multi-layered setting, and we focus on the problem of deciding whether a globally optimal assignment exists. We study this problem from the perspective of Parameterized Complexity: we consider several natural parameters such as the number of layers, the number of agents, the number of items, and the maximum length of a preference list. We present a comprehensive picture of the parameterized complexity of the problem with respect to these parameters.
AB - The Assignment problem is a fundamental and well-studied problem in the intersection of Social Choice, Computational Economics and Discrete Allocation. In the Assignment problem, a group of agents expresses preferences over a set of items, and the task is to find a pareto optimal allocation of items to agents. We introduce a generalized version of this problem, where each agent is equipped with multiple incomplete preference lists: each list (called a layer) is a ranking of items in a possibly different way according to a different criterion. We introduce the concept of global optimality, which extends the notion of pareto optimality to the multi-layered setting, and we focus on the problem of deciding whether a globally optimal assignment exists. We study this problem from the perspective of Parameterized Complexity: we consider several natural parameters such as the number of layers, the number of agents, the number of items, and the maximum length of a preference list. We present a comprehensive picture of the parameterized complexity of the problem with respect to these parameters.
UR - http://www.scopus.com/inward/record.url?scp=85113342089&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-030-82254-5_10
DO - https://doi.org/10.1007/978-3-030-82254-5_10
M3 - Conference contribution
SN - 9783030822538
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 160
EP - 177
BT - Multi-Agent Systems
A2 - Rosenfeld, Ariel
A2 - Talmon, Nimrod
PB - Springer
CY - Cham
T2 - 18th European Conference on Multi-Agent Systems, EUMAS 2021
Y2 - 28 June 2021 through 29 June 2021
ER -