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In this paper, we study some multiagent variants of the knapsack problem. Fluschnik et al. [AAAI 2019] considered the model in which every agent assigns some utility to every item. They studied three preference aggregation rules for finding…

Computer Science and Game Theory · Computer Science 2022-08-05 Sushmita Gupta , Pallavi Jain , Sanjay Seetharaman

In this paper we study a resource allocation problem that encodes correlation between items in terms of \conflict and maximizes the minimum utility of the agents under a conflict free allocation. Admittedly, the problem is computationally…

Data Structures and Algorithms · Computer Science 2023-09-12 Sushmita Gupta , Pallavi Jain , Saket Saurabh

It is challenging to quantify numerical preferences for different objectives in a multi-objective decision-making problem. However, the demonstrations of a user are often accessible. We propose an algorithm to infer linear preference…

Artificial Intelligence · Computer Science 2023-04-28 Junlin Lu

We consider a novel setting where a set of items are matched to the same set of agents repeatedly over multiple rounds. Each agent gets exactly one item per round, which brings interesting challenges to finding efficient and/or fair {\em…

Computer Science and Game Theory · Computer Science 2022-07-05 Ioannis Caragiannis , Shivika Narang

We investigate the problem of fairly allocating indivisible goods among interested agents using the concept of maximin share. Procaccia and Wang showed that while an allocation that gives every agent at least her maximin share does not…

Computer Science and Game Theory · Computer Science 2018-04-19 Warut Suksompong

Our work studies the fair allocation of indivisible items to a set of agents, and falls within the scope of establishing improved approximation guarantees. It is well known by now that the classic solution concepts in fair division, such as…

Computer Science and Game Theory · Computer Science 2023-08-10 Evangelos Markakis , Christodoulos Santorinaios

The fundamental assignment problem is in search of welfare maximization mechanisms to allocate items to agents when the private preferences over indivisible items are provided by self-interested agents. The mainstream mechanism…

Computer Science and Game Theory · Computer Science 2019-06-04 Yansong Gao , Jie Zhang

We consider multi-agent systems where agents' preferences are aggregated via sequential majority voting: each decision is taken by performing a sequence of pairwise comparisons where each comparison is a weighted majority vote among the…

Artificial Intelligence · Computer Science 2012-04-18 Maria Pini , Francesca Rossi , Brent Venable , Toby Walsh

A divisible budget must be allocated to several projects, and agents are asked for their opinion on how much they would give to each project. We consider that an agent is satisfied by a division of the budget if, for at least a certain…

Computer Science and Game Theory · Computer Science 2025-02-04 Laurent Gourvès , Michael Lampis , Nikolaos Melissinos , Aris Pagourtzis

A property $\Pi$ on a finite set $U$ is \emph{monotone} if for every $X \subseteq U$ satisfying $\Pi$, every superset $Y \subseteq U$ of $X$ also satisfies $\Pi$. Many combinatorial properties can be seen as monotone properties. The problem…

Data Structures and Algorithms · Computer Science 2024-10-03 Yasuaki Kobayashi , Kazuhiro Kurita , Kunihiro Wasa

We study an assortment optimization problem under a multi-purchase choice model in which customers choose a bundle of up to one product from each of two product categories. Different bundles have different utilities and the bundle price is…

Data Structures and Algorithms · Computer Science 2022-10-12 Xin Chen , Jiachun Li , Menglong Li , Tiancheng Zhao , Yuan Zhou

We consider ordinal approximation algorithms for a broad class of utility maximization problems for multi-agent systems. In these problems, agents have utilities for connecting to each other, and the goal is to compute a maximum-utility…

Multiagent Systems · Computer Science 2017-11-30 Ben Abramowitz , Elliot Anshelevich

We consider the Ordered Open End Bin Packing problem. Items of sizes in $(0,1]$ are presented one by one, to be assigned to bins in this order. An item can be assigned to any bin for which the current total size strictly below $1$. This…

Data Structures and Algorithms · Computer Science 2020-10-15 János Balogh , Leah Epstein , Asaf Levin

In reinforcement learning, robust policies for high-stakes decision-making problems with limited data are usually computed by optimizing the \emph{percentile criterion}. The percentile criterion is approximately solved by constructing an…

Machine Learning · Computer Science 2024-04-09 Elita A. Lobo , Cyrus Cousins , Yair Zick , Marek Petrik

In many real-world applications, the Pareto Set (PS) of a continuous multiobjective optimization problem can be a piecewise continuous manifold. A decision maker may want to find a solution set that approximates a small part of the PS and…

Neural and Evolutionary Computing · Computer Science 2024-04-02 Ping Guo , Qingfu Zhang , Xi Lin

We study the problem of fairly allocating a set of indivisible items among a set of agents. We consider the notion of (approximate) maximin share (MMS) and we provide an improved lower bound of $1/2$ (which is tight) for the case of…

Computer Science and Game Theory · Computer Science 2025-02-10 George Christodoulou , Vasilis Christoforidis , Symeon Mastrakoulis , Alkmini Sgouritsa

We study computational aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show…

Computer Science and Game Theory · Computer Science 2014-07-14 Haris Aziz , Serge Gaspers , Joachim Gudmundsson , Simon Mackenzie , Nicholas Mattei , Toby Walsh

We consider an assortment optimization problem where a customer chooses a single item from a sequence of sets shown to her, while limited inventories constrain the items offered to customers over time. In the special case where all of the…

Data Structures and Algorithms · Computer Science 2020-07-28 Elaheh Fata , Will Ma , David Simchi-Levi

Models often need to be constrained to a certain size for them to be considered interpretable. For example, a decision tree of depth 5 is much easier to understand than one of depth 50. Limiting model size, however, often reduces accuracy.…

Machine Learning · Computer Science 2020-07-02 Abhishek Ghose , Balaraman Ravindran

The Stable Roommates problem involves matching a set of agents into pairs based on the agents' strict ordinal preference lists. The matching must be stable, meaning that no two agents strictly prefer each other to their assigned partners. A…

Computer Science and Game Theory · Computer Science 2021-07-12 Michael McKay , David Manlove