Vincent Conitzer

research

∙ 07/11/2023

Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial

Peer review frequently follows a process where reviewers first provide i...

0 Ryan Liu, et al. ∙

research

∙ 07/11/2023

A Theory of Bounded Inductive Rationality

The dominant theories of rational choice assume logical omniscience. Tha...

0 Caspar Oesterheld, et al. ∙

research

∙ 06/08/2023

Steering No-Regret Learners to Optimal Equilibria

We consider the problem of steering no-regret-learning agents to play de...

0 Brian Hu Zhang, et al. ∙

research

∙ 06/08/2023

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games

We introduce a new approach for computing optimal equilibria via learnin...

0 Brian Hu Zhang, et al. ∙

research

∙ 05/28/2023

The Computational Complexity of Single-Player Imperfect-Recall Games

We study single-player extensive-form games with imperfect recall, such ...

0 Emanuel Tewolde, et al. ∙

research

∙ 05/18/2023

Game Theory with Simulation of Other Players

Game-theoretic interactions with AI agents could differ from traditional...

0 Vojtěch Kovařík, et al. ∙

research

∙ 11/26/2022

Similarity-based Cooperation

As machine learning agents act more autonomously in the world, they will...

0 Caspar Oesterheld, et al. ∙

research

∙ 07/22/2022

Tradeoffs in Preventing Manipulation in Paper Bidding for Reviewer Assignment

Many conferences rely on paper bidding as a key component of their revie...

0 Steven Jecmen, et al. ∙

research

∙ 07/07/2022

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria

Although it has been known since the 1970s that a globally optimal strat...

7 Scott Emmons, et al. ∙

research

∙ 06/24/2022

A Dataset on Malicious Paper Bidding in Peer Review

In conference peer review, reviewers are often asked to provide "bids" o...

0 Steven Jecmen, et al. ∙

research

∙ 05/16/2022

Efficient Algorithms for Planning with Participation Constraints

We consider the problem of planning with participation constraints intro...

0 Hanrui Zhang, et al. ∙

research

∙ 08/13/2021

Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design

Many scientific conferences employ a two-phase paper review process, whe...

0 Steven Jecmen, et al. ∙

research

∙ 05/13/2021

Automated Dynamic Mechanism Design

We study Bayesian automated mechanism design in unstructured dynamic env...

0 Hanrui Zhang, et al. ∙

research

∙ 04/30/2021

Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization

AI has the potential to revolutionize many areas of healthcare. Radiolog...

37 Michael Anis Mihdi Afnan, et al. ∙

research

∙ 04/29/2021

Computing Possible and Necessary Equilibrium Actions (and Bipartisan Set Winners)

In many multiagent environments, a designer has some, but limited contro...

0 Markus Brill, et al. ∙

research

∙ 04/12/2021

Automated Mechanism Design for Classification with Partial Verification

We study the problem of automated mechanism design with partial verifica...

0 Hanrui Zhang, et al. ∙

research

∙ 12/18/2020

Classification with Strategically Withheld Data

Machine learning techniques can be useful in applications such as credit...

0 Anilesh K. Krishnaswamy, et al. ∙

research

∙ 12/15/2020

Indecision Modeling

AI systems are often used to make or contribute to important decisions i...

14 Duncan C. McElfresh, et al. ∙

research

∙ 07/19/2020

Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss

In this paper, we investigate the problem of transforming an ε-BIC mecha...

0 Vincent Conitzer, et al. ∙

research

∙ 06/29/2020

Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments

We consider three important challenges in conference peer review: (i) re...

41 Steven Jecmen, et al. ∙

research

∙ 05/19/2020

Adapting a Kidney Exchange Algorithm to Align with Human Values

The efficient and fair allocation of limited resources is a classical pr...

12 Rachel Freedman, et al. ∙

research

∙ 01/13/2020

Artificial Artificial Intelligence: Measuring Influence of AI 'Assessments' on Moral Decision-Making

Given AI's growing role in modeling and improving decision-making, how a...

0 Lok Chan, et al. ∙

research

∙ 11/26/2018

Can Artificial Intelligence Do Everything That We Can?

In this article, I discuss what AI can and cannot yet do, and the implic...

0 Vincent Conitzer, et al. ∙

research

∙ 11/17/2018

Pacing Equilibrium in First-Price Auction Markets

In ad auctions--the prevalent monetization mechanism of Internet compani...

0 Vincent Conitzer, et al. ∙

research

∙ 05/06/2018

The Exact Computational Complexity of Evolutionarily Stable Strategies

While the computational complexity of many game-theoretic solution conce...

0 Vincent Conitzer, et al. ∙

research

∙ 09/21/2017

Complexity of Scheduling Charging in the Smart Grid

In the smart grid, the intent is to use flexibility in demand, both to b...

0 Mathijs de Weerdt, et al. ∙

research

∙ 07/31/2014

Justified Representation in Approval-Based Committee Voting

We consider approval-based committee voting, i.e. the setting where each...

0 Haris Aziz, et al. ∙

research

∙ 01/16/2014

Determining Possible and Necessary Winners Given Partial Orders

Usually a voting rule requires agents to give their preferences as linea...

0 Lirong Xia, et al. ∙

research

∙ 07/04/2012

Common Voting Rules as Maximum Likelihood Estimators

Voting is a very general method of preference aggregation. A voting rule...

0 Vincent Conitzer, et al. ∙

research

∙ 06/27/2011

Dominating Manipulations in Voting with Partial Information

We consider manipulation problems when the manipulator only has partial ...

0 Vincent Conitzer, et al. ∙

research

∙ 04/22/2009

Incentive Compatible Budget Elicitation in Multi-unit Auctions

In this paper, we consider the problem of designing incentive compatible...

0 Sayan Bhattacharya, et al. ∙

research

∙ 07/07/2003

Universal Voting Protocol Tweaks to Make Manipulation Hard

Voting is a general method for preference aggregation in multiagent sett...

0 Vincent Conitzer, et al. ∙

research

∙ 07/07/2003

Complexity of Determining Nonemptiness of the Core

Coalition formation is a key problem in automated negotiation among self...

0 Vincent Conitzer, et al. ∙

research

∙ 07/03/2003

BL-WoLF: A Framework For Loss-Bounded Learnability In Zero-Sum Games

We present BL-WoLF, a framework for learnability in repeated zero-sum ga...

0 Vincent Conitzer, et al. ∙

research

∙ 07/02/2003

How many candidates are needed to make elections hard to manipulate?

In multiagent settings where the agents have different preferences, pref...

0 Vincent Conitzer, et al. ∙

research

∙ 07/01/2003

AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Opponents

A satisfactory multiagent learning algorithm should, at a minimum, lear...

0 Vincent Conitzer, et al. ∙

research

∙ 05/29/2002

Vote Elicitation: Complexity and Strategy-Proofness

Preference elicitation is a central problem in AI, and has received sign...

0 Vincent Conitzer, et al. ∙

research

∙ 05/28/2002

Complexity of Mechanism Design

The aggregation of conflicting preferences is a central problem in multi...

0 Vincent Conitzer, et al. ∙

research

∙ 05/28/2002

Complexity Results about Nash Equilibria

Noncooperative game theory provides a normative framework for analyzing ...

0 Vincent Conitzer, et al. ∙

Vincent Conitzer

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