no code implementations • ICML 2020 • Hanrui Zhang, Vincent Conitzer
We study problems where a learner aims to learn the valuations of an agent by observing which goods he buys under varying price vectors.
no code implementations • ICML 2020 • Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang
We study the problem of learning opinions in social networks.
no code implementations • 2 Mar 2025 • Vijay Keswani, Vincent Conitzer, Walter Sinnott-Armstrong, Breanna K. Nguyen, Hoda Heidari, Jana Schaich Borg
A growing body of work in Ethical AI attempts to capture human moral judgments through simple computational models.
no code implementations • 25 Feb 2025 • Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm
At the heart of our approach is a polynomial-time algorithm for computing an expected fixed point of any $\phi : \mathcal{X} \to \mathcal{X}$ based on the ellipsoid against hope (EAH) algorithm of Papadimitriou and Roughgarden (JACM '08).
no code implementations • 25 Feb 2025 • Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm
Variational inequalities (VIs) encompass many fundamental problems in diverse areas ranging from engineering to economics and machine learning.
no code implementations • 19 Feb 2025 • Lewis Hammond, Alan Chan, Jesse Clifton, Jason Hoelscher-Obermaier, Akbir Khan, Euan McLean, Chandler Smith, Wolfram Barfuss, Jakob Foerster, Tomáš Gavenčiak, The Anh Han, Edward Hughes, Vojtěch Kovařík, Jan Kulveit, Joel Z. Leibo, Caspar Oesterheld, Christian Schroeder de Witt, Nisarg Shah, Michael Wellman, Paolo Bova, Theodor Cimpeanu, Carson Ezell, Quentin Feuillade-Montixi, Matija Franklin, Esben Kran, Igor Krawczuk, Max Lamparth, Niklas Lauffer, Alexander Meinke, Sumeet Motwani, Anka Reuel, Vincent Conitzer, Michael Dennis, Iason Gabriel, Adam Gleave, Gillian Hadfield, Nika Haghtalab, Atoosa Kasirzadeh, Sébastien Krier, Kate Larson, Joel Lehman, David C. Parkes, Georgios Piliouras, Iyad Rahwan
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity.
no code implementations • 16 Feb 2025 • Jiayuan Liu, Mingyu Guo, Vincent Conitzer
The code generation capabilities of LLMs enable the discovery of novel and interpretable solutions, bridging the symbolic logic of mechanism design and the generative power of modern AI.
no code implementations • 15 Jan 2025 • Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Tuomas Sandholm, Vincent Conitzer
Strategic interactions can be represented more concisely, and analyzed and solved more efficiently, if we are aware of the symmetries within the multiagent system.
no code implementations • 23 Dec 2024 • Scott Emmons, Caspar Oesterheld, Vincent Conitzer, Stuart Russell
We show that this incentive for interference goes away if the human is playing optimally, or if we introduce a communication channel for the human to communicate their preferences to the assistant.
no code implementations • 22 Dec 2024 • Hanrui Zhang, Yu Cheng, Vincent Conitzer
Our algorithm for SEFCE is the first polynomial-time algorithm for equilibrium computation with commitment in such a general class of stochastic games.
no code implementations • 19 Dec 2024 • Emery Cooper, Caspar Oesterheld, Vincent Conitzer
Finally, we explore the limits of simulation-based program equilibrium, showing that the Tennenholtz folk theorem cannot be attained by simulation-based programs without access to shared randomness.
no code implementations • 7 Nov 2024 • Emery Cooper, Caspar Oesterheld, Vincent Conitzer
If so, then causal decision theory might recommend one-boxing in order to cause the predictor to fill the opaque box.
no code implementations • 18 Oct 2024 • Vojtech Kovarik, Nathaniel Sauerberg, Lewis Hammond, Vincent Conitzer
As positive results, we establish that mixed-strategy simulation can improve social welfare if the simulator has the option to scale their level of trust, if the players face challenges with both trust and coordination, or if maintaining some level of privacy is essential for enabling cooperation.
no code implementations • 5 Aug 2024 • Kyle Boerstler, Vijay Keswani, Lok Chan, Jana Schaich Borg, Vincent Conitzer, Hoda Heidari, Walter Sinnott-Armstrong
If participants' moral responses are unstable in such ways, it would raise important methodological and theoretical issues for how participants' true moral preferences, opinions, and judgments can be ascertained.
no code implementations • 26 Jul 2024 • Vijay Keswani, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong
In this work, we argue that the use of active learning for moral preference elicitation relies on certain assumptions about the underlying moral preferences, which can be violated in practice.
no code implementations • 10 Jul 2024 • Vincent Conitzer
Given this, why should we ever automate moral decision making -- is it not better to leave all moral decision making to humans?
no code implementations • 23 Jun 2024 • Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Manolis Zampetakis, Tuomas Sandholm, Paul W. Goldberg, Vincent Conitzer
We investigate optimal decision making under imperfect recall, that is, when an agent forgets information it once held before.
no code implementations • 16 Apr 2024 • Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker
Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text.
no code implementations • 12 Feb 2024 • Vojtech Kovarik, Caspar Oesterheld, Vincent Conitzer
In this paper, we study an interaction between AI agents where the agents run a recursive joint simulation.
no code implementations • 11 Jul 2023 • Caspar Oesterheld, Abram Demski, Vincent Conitzer
In this paper, we develop a theory of rational decision making that does not assume logical omniscience.
no code implementations • 28 May 2023 • Emanuel Tewolde, Caspar Oesterheld, Vincent Conitzer, Paul W. Goldberg
For such games, two natural equilibrium concepts have been proposed as alternative solution concepts to ex-ante optimality.
no code implementations • 22 Jul 2022 • Steven Jecmen, Nihar B. Shah, Fei Fang, Vincent Conitzer
Many conferences rely on paper bidding as a key component of their reviewer assignment procedure.
1 code implementation • 7 Jul 2022 • Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, Stuart Russell
In this work, we show that any locally optimal symmetric strategy profile is also a (global) Nash equilibrium.
1 code implementation • 24 Jun 2022 • Steven Jecmen, Minji Yoon, Vincent Conitzer, Nihar B. Shah, Fei Fang
The performance of these detection algorithms can be taken as a baseline for future research on detecting malicious bidding.
no code implementations • 16 May 2022 • Hanrui Zhang, Yu Cheng, Vincent Conitzer
Our approach can also be extended to the (discounted) infinite-horizon case, for which we give an algorithm that runs in time polynomial in the size of the input and $\log(1/\varepsilon)$, and returns a policy that is optimal up to an additive error of $\varepsilon$.
1 code implementation • 13 Aug 2021 • Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah
Many scientific conferences employ a two-phase paper review process, where some papers are assigned additional reviewers after the initial reviews are submitted.
no code implementations • Proceedings of the AAAI Conference on Artificial Intelligence 2021 • Hanrui Zhang, Vincent Conitzer
We give a sample complexity bound that is, curiously, independent of the hypothesis class, for the ERM principle restricted to incentivecompatible classifiers.
no code implementations • 30 Apr 2021 • Michael Anis Mihdi Afnan, Cynthia Rudin, Vincent Conitzer, Julian Savulescu, Abhishek Mishra, Yanhe Liu, Masoud Afnan
We then consider the broader ethical issues involved.
no code implementations • 12 Apr 2021 • Hanrui Zhang, Yu Cheng, Vincent Conitzer
We study the problem of automated mechanism design with partial verification, where each type can (mis)report only a restricted set of types (rather than any other type), induced by the principal's limited verification power.
1 code implementation • 18 Dec 2020 • Anilesh K. Krishnaswamy, Haoming Li, David Rein, Hanrui Zhang, Vincent Conitzer
To this end, we present {\sc IC-LR}, a modification of Logistic Regression that removes the incentive to strategically drop features.
1 code implementation • 15 Dec 2020 • Duncan C McElfresh, Lok Chan, Kenzie Doyle, Walter Sinnott-Armstrong, Vincent Conitzer, Jana Schaich Borg, John P Dickerson
The philosophy and psychology literature shows that indecision is a measurable and nuanced behavior -- and that there are several different reasons people are indecisive.
2 code implementations • NeurIPS 2020 • Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang
We further consider the problem of restricting the joint probability that certain suspect pairs of reviewers are assigned to certain papers, and show that this problem is NP-hard for arbitrary constraints on these joint probabilities but efficiently solvable for a practical special case.
1 code implementation • 19 May 2020 • Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer
In kidney exchanges, a central market maker allocates living kidney donors to patients in need of an organ.
no code implementations • NeurIPS 2019 • Hanrui Zhang, Yu Cheng, Vincent Conitzer
In other settings, the principal may not even be able to observe samples directly; instead, she must rely on signals that the agent is able to send based on the samples that he obtains, and he will choose these signals strategically.
no code implementations • 21 Sep 2017 • Mathijs de Weerdt, Michael Albert, Vincent Conitzer
In the smart grid, the intent is to use flexibility in demand, both to balance demand and supply as well as to resolve potential congestion.
no code implementations • 22 Jun 2017 • Vincent Conitzer, Christian Kroer, Eric Sodomka, Nicolas E. Stier-Moses
Although we show that computing either a social-welfare-maximizing or a revenue-maximizing pacing equilibrium is NP-hard, we present a mixed-integer program (MIP) that can be used to find equilibria optimizing several relevant objectives.
Computer Science and Game Theory
no code implementations • 19 May 2016 • Vincent Conitzer
In this article, I discuss how the AI community views concerns about the emergence of superintelligent AI and related philosophical issues.