TY - GEN
T1 - More Effort Towards Multiagent Knapsack
AU - Gupta, Sushmita
AU - Jain, Pallavi
AU - Seetharaman, Sanjay
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - In this paper, we study two multiagent variants of the knapsack problem. Fluschnik et al. [AAAI 2019] studied the model in which each agent expresses its preference by assigning a utility to every item. They studied three preference aggregation rules for finding a subset (knapsack) of items: individually best, diverse, and Nash welfare-based. Informally, diversity is achieved by satisfying as many agents as possible. Motivated by the application of aggregation operators in multiwinner elections, we extend the study from diverse aggregation rule to Median and Best scoring functions. We study the computational and parameterized complexity of the problem with respect to some natural parameters, namely, the number of agents, the number of items, and the distance from an easy instance. We also study the complexity of the problem under domain restrictions. Furthermore, we present significantly faster parameterized algorithms with respect to the number of agents for the diverse aggregation rule.
AB - In this paper, we study two multiagent variants of the knapsack problem. Fluschnik et al. [AAAI 2019] studied the model in which each agent expresses its preference by assigning a utility to every item. They studied three preference aggregation rules for finding a subset (knapsack) of items: individually best, diverse, and Nash welfare-based. Informally, diversity is achieved by satisfying as many agents as possible. Motivated by the application of aggregation operators in multiwinner elections, we extend the study from diverse aggregation rule to Median and Best scoring functions. We study the computational and parameterized complexity of the problem with respect to some natural parameters, namely, the number of agents, the number of items, and the distance from an easy instance. We also study the complexity of the problem under domain restrictions. Furthermore, we present significantly faster parameterized algorithms with respect to the number of agents for the diverse aggregation rule.
KW - Complexity
KW - Social choice
KW - Voting
UR - http://www.scopus.com/inward/record.url?scp=85146698848&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-23101-8_4
DO - 10.1007/978-3-031-23101-8_4
M3 - Conference contribution
AN - SCOPUS:85146698848
SN - 9783031231001
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 47
EP - 62
BT - SOFSEM 2023
A2 - Gasieniec, Leszek
PB - Springer Science and Business Media Deutschland GmbH
T2 - 48th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2023
Y2 - 15 January 2023 through 18 January 2023
ER -