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Most work on manipulation assumes that all preferences are known to the manipulators. However, in many settings elections are open and sequential, and manipulators may know the already cast votes but may not know the future votes. We…

Computer Science and Game Theory · Computer Science 2013-10-28 Edith Hemaspaandra , Lane A. Hemaspaandra , Joerg Rothe

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can…

Adaptation and Self-Organizing Systems · Physics 2018-02-07 Nathaniel Rupprecht , Dervis Can Vural

In multiagent systems, agents often have to rely on other agents to reach their goals, for example when they lack a needed resource or do not have the capability to perform a required action. Agents therefore need to cooperate. Then, some…

Artificial Intelligence · Computer Science 2020-10-08 Antonis Bikakis , Patrice Caire

While manipulative attacks on elections have been well-studied, only recently has attention turned to attacks that account for geographic information, which are extremely common in the real world. The most well known in the media is…

Computer Science and Game Theory · Computer Science 2020-03-17 Zack Fitzsimmons , Omer Lev

We study the distributed facility location problem, where a set of agents with positions on the line of real numbers are partitioned into disjoint districts, and the goal is to choose a point to satisfy certain criteria, such as optimize an…

Computer Science and Game Theory · Computer Science 2023-01-05 Aris Filos-Ratsikas , Panagiotis Kanellopoulos , Alexandros A. Voudouris , Rongsen Zhang

We study the problem of an organization that matches agents to objects where agents have preference rankings over objects and the organization uses algorithms to construct a ranking over objects on behalf of each agent. Our new framework…

Theoretical Economics · Economics 2025-08-12 Terence Highsmith

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Computer Science 2014-08-12 Aristide Tossou , Christos Dimitrakakis

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Statistics 2013-07-16 Aristide C. Y. Tossou , Christos Dimitrakakis

Coalitional manipulation in voting is considered to be any scenario in which a group of voters decide to misrepresent their vote in order to secure an outcome they all prefer to the first outcome of the election when they vote honestly. The…

Theoretical Economics · Economics 2020-09-28 Mostapha Diss , Boris Tsvelikhovskiy

When consequential decisions are informed by algorithmic input, individuals may feel compelled to alter their behavior in order to gain a system's approval. Models of agent responsiveness, termed "strategic manipulation," analyze the…

Machine Learning · Computer Science 2019-05-13 Lily Hu , Nicole Immorlica , Jennifer Wortman Vaughan

We study the power of (competitive) algorithms with predictions in a multiagent setting. We introduce a two predictor framework, that assumes that agents use one predictor for their future (self) behavior, and one for the behavior of the…

Multiagent Systems · Computer Science 2025-07-18 Gabriel Istrate , Cosmin Bonchis , Victor Bogdan

We study mechanism design when a designer repeatedly uses a fixed mechanism to interact with strategic agents who learn from observing their allocations. We introduce a static framework, calibrated mechanism design, requiring mechanisms to…

Theoretical Economics · Economics 2026-02-19 Laura Doval , Alex Smolin

Knockout tournaments, also known as single-elimination or cup tournaments, are a popular form of sports competitions. In the standard probabilistic setting, for each pairing of players, one of the players wins the game with a certain (a…

Data Structures and Algorithms · Computer Science 2024-12-17 Juhi Chaudhary , Hendrik Molter , Meirav Zehavi

In this paper I present several algorithmic techniques for improving the decision process of multiple types of agents behaving in environments where their interests are in conflict. The interactions between the agents are modelled by using…

Computer Science and Game Theory · Computer Science 2009-08-04 Mugurel Ionut Andreica

Manipulation is a problem of fundamental importance in the context of voting in which the voters exercise their votes strategically instead of voting honestly to prevent selection of an alternative that is less preferred. The…

Multiagent Systems · Computer Science 2015-02-17 Palash Dey , Neeldhara Misra , Y. Narahari

The probability of a given candidate winning a future election is worked out in closed form as a function of (i) the current support rates for each candidate, (ii) the relative positioning of the candidates within the political spectrum,…

Probability · Mathematics 2025-04-25 Dorje C. Brody , Tomooki Yuasa

We study the effects of campaigning, where the society is partitioned into voter clusters and a diffusion process propagates opinions in a network connecting the clusters. Our model is very powerful and can incorporate many campaigning…

Multiagent Systems · Computer Science 2020-10-05 Piotr Faliszewski , Rica Gonen , Martin Koutecký , Nimrod Talmon

Voting is a simple mechanism to aggregate the preferences of agents. Many voting rules have been shown to be NP-hard to manipulate. However, a number of recent theoretical results suggest that this complexity may only be in the worst-case…

Artificial Intelligence · Computer Science 2009-05-25 Toby Walsh

We study social choice rules under the utilitarian distortion framework, with an additional metric assumption on the agents' costs over the alternatives. In this approach, these costs are given by an underlying metric on the set of all…

Computer Science and Game Theory · Computer Science 2021-01-15 Ashish Goel , Anilesh Kollagunta Krishnaswamy , Kamesh Munagala

Schulze and ranked-pairs elections have received much attention recently, and the former has quickly become a quite widely used election system. For many cases these systems have been proven resistant to bribery, control, or manipulation,…

Computer Science and Game Theory · Computer Science 2014-06-24 Lane A. Hemaspaandra , Rahman Lavaee , Curtis Menton
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