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A family of models of individual discrete choice are constructed by means of statistical averaging of choices made by a subject in a reinforcement learning process, where the subject has short, k-term memory span. The choice probabilities…

Econometrics · Economics 2019-08-20 Misha Perepelitsa

This paper addresses the problem of sequential submodular maximization: selecting and ranking items in a sequence to optimize some composite submodular function. In contrast to most of the previous works, which assume access to the utility…

Machine Learning · Computer Science 2024-09-10 Jing Yuan , Shaojie Tang

This study considers the method to derive a ranking of alternatives by aggregating the rankings submitted by several individuals who may not evaluate all of them. The collection of subsets of alternatives that individuals (can) evaluate is…

Theoretical Economics · Economics 2024-09-18 Yasunori Okumura

We consider the challenge of AI value alignment with multiple individuals that have different reward functions and optimal policies in an underlying Markov decision process. We formalize this problem as one of policy aggregation, where the…

Artificial Intelligence · Computer Science 2024-11-07 Parand A. Alamdari , Soroush Ebadian , Ariel D. Procaccia

Public funding processes demand fairness, learning, and outcomes that participants can understand. We introduce Komitee Equal Shares, a priceable virtual-budget allocation framework that integrates two signals: in voter mode, participants…

Human-Computer Interaction · Computer Science 2025-10-03 Joshua C. Yang , Noemi Scheurer

We study the problem of aggregating distributions, such as budget proposals, into a collective distribution. An ideal aggregation mechanism would be Pareto efficient, strategyproof, and fair. Most previous work assumes that agents evaluate…

Theoretical Economics · Economics 2025-12-24 Felix Brandt , Matthias Greger , Erel Segal-Halevi , Warut Suksompong

Submodular functions -- functions exhibiting diminishing returns -- are central to machine learning. When the objective is monotone and non-negative, the greedy algorithm achieves a tight $63\%$ approximation. But many practical objectives…

Machine Learning · Computer Science 2026-05-11 Yixin Chen , Alan Kuhnle

Assortment optimization refers to the problem of designing a slate of products to offer potential customers, such as stocking the shelves in a convenience store. The price of each product is fixed in advance, and a probabilistic choice…

Computer Science and Game Theory · Computer Science 2017-11-09 Nicole Immorlica , Brendan Lucier , Jieming Mao , Vasilis Syrgkanis , Christos Tzamos

This paper studies a setting in which multiple suppliers compete for a buyer's procurement business. The buyer faces uncertain demand and there is a requirement to reserve capacity in advance of knowing the demand. Each supplier has costs…

Computer Science and Game Theory · Computer Science 2019-05-28 Edward Anderson , Bo Chen , Lusheng Shao

Consensus halving refers to the problem of dividing a resource into two parts so that every agent values both parts equally. Prior work has shown that when the resource is represented by an interval, a consensus halving with at most $n$…

Computer Science and Game Theory · Computer Science 2022-11-22 Paul W. Goldberg , Alexandros Hollender , Ayumi Igarashi , Pasin Manurangsi , Warut Suksompong

Decentralized resource allocation is a key problem for large-scale autonomic (or self-managing) computing systems. Motivated by a data center scenario, we explore efficient techniques for resolving resource conflicts via cooperative…

Computer Science and Game Theory · Computer Science 2012-12-12 Craig Boutilier , Rajarshi Das , Jeffrey O. Kephart , Gerald Tesauro , William E. Walsh

We study non-monetary mechanisms for the fair and efficient allocation of reusable public resources, i.e., resources used for varying durations. We consider settings where a limited resource is repeatedly shared among a set of agents, each…

Computer Science and Game Theory · Computer Science 2023-10-17 Siddhartha Banerjee , Giannis Fikioris , Éva Tardos

Two of the main factors shaping an individual's opinion are social coordination and personal preferences, or personal biases. To understand the role of those and that of the topology of the network of interactions, we study an extension of…

Physics and Society · Physics 2023-06-07 Filippo Zimmaro , Pierluigi Contucci , János Kertész

We study procurement auctions, where an auctioneer seeks to acquire services from strategic sellers with private costs. The quality of services is measured by a submodular function known to the auctioneer. Our goal is to design…

Computer Science and Game Theory · Computer Science 2024-11-21 Yuan Deng , Amin Karbasi , Vahab Mirrokni , Renato Paes Leme , Grigoris Velegkas , Song Zuo

Multimodal learning considers learning from multi-modality data, aiming to fuse heterogeneous sources of information. However, it is not always feasible to leverage all available modalities due to memory constraints. Further, training on…

Machine Learning · Computer Science 2022-10-25 Runxiang Cheng , Gargi Balasubramaniam , Yifei He , Yao-Hung Hubert Tsai , Han Zhao

In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs…

Machine Learning · Computer Science 2023-02-02 Alessio Benavoli , Dario Azzimonti , Dario Piga

How should one combine noisy information from diverse sources to make an inference about an objective ground truth? This frequently recurring, normative question lies at the core of statistics, machine learning, policy-making, and everyday…

Multiagent Systems · Computer Science 2020-01-29 Silviu Pitis , Michael R. Zhang

How to utilize an allocated budget effectively for branding and promotion of a commercial house is an important problem, particularly when multiple advertising media are available. There exist multiple such media, and among them, two…

Data Structures and Algorithms · Computer Science 2026-04-02 Dildar Ali , Ansh Jasrotia , Abishek Salaria , Suman Banerjee

Subset selection tasks, arise in recommendation systems and search engines and ask to select a subset of items that maximize the value for the user. The values of subsets often display diminishing returns, and hence, submodular functions…

Machine Learning · Computer Science 2023-05-05 Anay Mehrotra , Nisheeth K. Vishnoi

We design two mechanisms that ensure that the majority preferred option wins in all equilibria. The first one is a simultaneous game where agents choose other agents to cooperate with on top of the vote for an alternative, thus overcoming…

Theoretical Economics · Economics 2023-10-12 Kirneva Margarita , Núñez Matías