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Related papers: Maxmin Participatory Budgeting

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Allocating conflicting jobs among individuals while respecting a budget constraint for each individual is an optimization problem that arises in various real-world scenarios. In this paper, we consider the situation where each individual…

Data Structures and Algorithms · Computer Science 2024-02-06 Sushmita Gupta , Pallavi Jain , A. Mohanapriya , Vikash Tripathi

We introduce a family of normative principles to assess fairness in the context of participatory budgeting. These principles are based on the fundamental idea that budget allocations should be fair in terms of the resources invested into…

Computer Science and Game Theory · Computer Science 2023-02-21 Jan Maly , Simon Rey , Ulle Endriss , Martin Lackner

We present a new model of collective decision making that captures important crowd-funding and donor coordination scenarios. In the setting, there is a set of projects (each with its own cost) and a set of agents (that have their budgets as…

Computer Science and Game Theory · Computer Science 2021-01-29 Haris Aziz , Aditya Ganguly

Participatory budgeting, as a paradigm for democratic innovations, engages citizens in the distribution of a public budget to projects, which they propose and vote for implementation. So far, voting algorithms have been proposed and studied…

Multiagent Systems · Computer Science 2024-10-30 Sajan Maharjan , Srijoni Majumdar , Evangelos Pournaras

In project scheduling under processing times uncertainty, the Anchor-Robust Project Scheduling Problem is to find a baseline schedule of bounded makespan and a max-weight subset of jobs whose starting times are guaranteed. The problem was…

Optimization and Control · Mathematics 2021-06-24 Pascale Bendotti , Philippe Chrétienne , Pierre Fouilhoux , Adèle Pass-Lanneau

Decision making under uncertainty is at the heart of any autonomous system acting with imperfect information. The cost of solving the decision making problem is exponential in the action and observation spaces, thus rendering it unfeasible…

Artificial Intelligence · Computer Science 2024-06-18 Tom Yotam , Vadim Indelman

In this work, we study the Stochastic Budgeted Multi-round Submodular Maximization (SBMSm) problem, where we aim to adaptively maximize the sum, over multiple rounds, of a monotone and submodular objective function defined on subsets of…

Data Structures and Algorithms · Computer Science 2024-09-26 Vincenzo Auletta , Diodato Ferraioli , Cosimo Vinci

We contribute to the programme of lifting proportionality axioms from the multi-winner voting setting to participatory budgeting. We define novel proportionality axioms for participatory budgeting and test them on known…

Computer Science and Game Theory · Computer Science 2022-05-05 Maaike Los , Zoé Christoff , Davide Grossi

We study a participatory budgeting problem of aggregating the preferences of agents and dividing a budget over the projects. A budget division solution is a probability distribution over the projects. The main purpose of our study concerns…

Computer Science and Game Theory · Computer Science 2020-11-02 Zhongzheng Tang , Chenhao Wang , Mengqi Zhang

We study the Maximum Budgeted Allocation problem, i.e., the problem of selling a set of $m$ indivisible goods to $n$ players, each with a separate budget, such that we maximize the collected revenue. Since the natural assignment LP is known…

Data Structures and Algorithms · Computer Science 2014-03-31 Christos Kalaitzis , Aleksander Mcadry , Alantha Newman , Lukáš Poláček , Ola Svensson

We study the Maximum Budgeted Allocation problem, which is the problem of assigning indivisible items to players with budget constraints. In its most general form, an instance of the MBA problem might include many different prices for the…

Data Structures and Algorithms · Computer Science 2015-12-01 Christos Kalaitzis

This paper focuses on managing the cost of deliberation before action. In many problems, the overall quality of the solution reflects costs incurred and resources consumed in deliberation as well as the cost and benefit of execution, when…

Artificial Intelligence · Computer Science 2013-04-05 David Einav , Michael R. Fehling

We study a participatory budgeting problem, where a set of strategic agents wish to split a divisible budget among different projects, by aggregating their proposals on a single division. Unfortunately, the straight-forward rule that…

Computer Science and Game Theory · Computer Science 2022-03-21 Ioannis Caragiannis , George Christodoulou , Nicos Protopapas

We study a class of procurement auctions with a budget constraint, where an auctioneer is interested in buying resources or services from a set of agents. Ideally, the auctioneer would like to select a subset of the resources so as to…

Computer Science and Game Theory · Computer Science 2017-10-10 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

The winner determination problems of many attractive multi-winner voting rules are NP-complete. However, they often admit polynomial-time algorithms when restricting inputs to be single-peaked. Commonly, such algorithms employ dynamic…

Computer Science and Game Theory · Computer Science 2021-04-20 Dominik Peters

Possibilistic and qualitative POMDPs (pi-POMDPs) are counterparts of POMDPs used to model situations where the agent's initial belief or observation probabilities are imprecise due to lack of past experiences or insufficient data…

Artificial Intelligence · Computer Science 2013-09-27 Nicolas Drougard , Florent Teichteil-Konigsbuch , Jean-Loup Farges , Didier Dubois

To choose a suitable multiwinner voting rule is a hard and ambiguous task. Depending on the context, it varies widely what constitutes the choice of an ``optimal'' subset of alternatives. In this paper, we provide a quantitative analysis of…

Multiagent Systems · Computer Science 2020-09-01 Martin Lackner , Piotr Skowron

In fair division, equitability dictates that each participant receives the same level of utility. In this work, we study equitable allocations of indivisible goods among agents with additive valuations. While prior work has studied…

Computer Science and Game Theory · Computer Science 2019-05-28 Rupert Freeman , Sujoy Sikdar , Rohit Vaish , Lirong Xia

The max-product {belief propagation} (BP) is a popular message-passing heuristic for approximating a maximum-a-posteriori (MAP) assignment in a joint distribution represented by a graphical model (GM). In the past years, it has been shown…

Artificial Intelligence · Computer Science 2017-06-29 Sejun Park , Jinwoo Shin

Persuasion studies how an informed principal may influence the behavior of agents by the strategic provision of payoff-relevant information. We focus on the fundamental multi-receiver model by Arieli and Babichenko (2019), in which there…

Computer Science and Game Theory · Computer Science 2020-04-01 Matteo Castiglioni , Andrea Celli , Nicola Gatti