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We study a setting where Bayesian agents with a common prior have private information related to an event's outcome and sequentially make public announcements relating to their information. Our main result shows that when agents' private…

Computer Science and Game Theory · Computer Science 2022-11-28 Yuqing Kong , Grant Schoenebeck

We study a problem where a group of agents has to decide how a joint reward should be shared among them. We focus on settings where the share that each agent receives depends on the subjective opinions of its peers concerning that agent's…

Computer Science and Game Theory · Computer Science 2013-05-23 Arthur Carvalho , Kate Larson

We study the emergence of conformity preferences in an environment in which agents choose effort under heterogeneous, possibly misspecified returns, and social interactions do not directly affect material payoffs. Some agents choose effort…

Theoretical Economics · Economics 2026-05-05 Paolo Pin , Roberto Rozzi

We consider a peer-to-peer electricity market, where agents hold private information that they might not want to share. The problem is modeled as a noncooperative communication game, which takes the form of a Generalized Nash Equilibrium…

Computer Science and Game Theory · Computer Science 2021-01-19 Ilia Shilov , Hélène Le Cadre , Ana Bušic

We study allocation problems without monetary transfers where agents have correlated types, i.e., hold private information about one another. Such peer information is relevant in various settings, including science funding, allocation of…

Theoretical Economics · Economics 2025-03-21 Axel Niemeyer , Justus Preusser

Prediction markets elicit and aggregate beliefs by paying agents based on how close their predictions are to a verifiable future outcome. However, outcomes of many important questions are difficult to verify or unverifiable, in that the…

Computer Science and Game Theory · Computer Science 2025-02-19 Siddarth Srinivasan , Ezra Karger , Yiling Chen

Common sense suggests that when individuals explain why they believe something, we can arrive at more accurate conclusions than when they simply state what they believe. Yet, there is no known mechanism that provides incentives to elicit…

Computer Science and Game Theory · Computer Science 2025-02-20 Siddarth Srinivasan , Ezra Karger , Michiel Bakker , Yiling Chen

There are several aspects of data markets that distinguish them from a typical commodity market: asymmetric information, the non-rivalrous nature of data, and informational externalities. Formally, this gives rise to a new class of games…

Computer Science and Game Theory · Computer Science 2023-03-29 Samir Wadhwa , Roy Dong

The evaluation and post-training of large language models (LLMs) rely on supervision, but strong supervision for difficult tasks is often unavailable, especially when evaluating frontier models. In such cases, models are demonstrated to…

Machine Learning · Computer Science 2026-01-29 Tianyi Alex Qiu , Micah Carroll , Cameron Allen

An informed Advisor and an uninformed Decision-Maker, with conflicting interests, engage in repeated cheap talk communication in always new decision problems. While the Decision-Maker's optimal payoff is attainable in some subgame-perfect…

Theoretical Economics · Economics 2025-08-04 Steven Kivinen , Christoph Kuzmics

A sender first publicly commits to an experiment and then can privately run additional experiments and selectively disclose their outcomes to a receiver. The sender has private information about the maximal number of additional experiments…

Theoretical Economics · Economics 2026-01-12 Yifan Dai , Drew Fudenberg , Harry Pei

We consider two-alternative elections where voters' preferences depend on a state variable that is not directly observable. Each voter receives a private signal that is correlated to the state variable. Voters may be "contingent" with…

Computer Science and Game Theory · Computer Science 2022-06-15 Grant Schoenebeck , Biaoshuai Tao

Classic results show that even an arbitrarily small correlation across bidders' information can enable full surplus extraction in auctions and related mechanism design settings. Motivated by this fragility, we study the information…

Computer Science and Game Theory · Computer Science 2026-04-28 Boyu Liu , Wei Tang , Zihe Wang , Shuo Zhang

We study a cheap-talk game where two experts first choose what information to acquire and then offer advice to a decision-maker whose actions affect the welfare of all. The experts cannot commit to reporting strategies. Yet, we show that…

Theoretical Economics · Economics 2021-04-08 Alp Atakan , Mehmet Ekmekci , Ludovic Renou

Recent advances in multi-task peer prediction have greatly expanded our knowledge about the power of multi-task peer prediction mechanisms. Various mechanisms have been proposed in different settings to elicit different types of…

Computer Science and Game Theory · Computer Science 2021-06-08 Shuran Zheng , Fang-Yi Yu , Yiling Chen

In practice, most auction mechanisms are not strategy-proof, so equilibrium analysis is required to predict bidding behavior. In many auctions, though, an exact equilibrium is not known and one would like to understand whether -- manually…

Computer Science and Game Theory · Computer Science 2024-08-22 Fabian R. Pieroth , Tuomas Sandholm

We study strategic candidate nomination by parties in elections decided by Plurality voting. Each party selects a nominee before the election, and the winner is chosen from the nominated candidates based on the voters' preferences. We…

Computer Science and Game Theory · Computer Science 2025-11-17 Piotr Faliszewski , Stanislaw Kazmierowski , Grzegorz Lisowski , Ildiko Schlotter , Paolo Turrini

In many settings, multiple uninformed agents bargain simultaneously with a single informed agent in each of multiple periods. For example, workers and firms negotiate each year over salaries, and the firm has private information about the…

Theoretical Economics · Economics 2020-11-10 Quitzé Valenzuela-Stookey

In socio-technical multi-agent systems, deception exploits privileged information to induce false beliefs in "victims," keeping them oblivious and leading to outcomes detrimental to them or advantageous to the deceiver. We consider…

Systems and Control · Electrical Eng. & Systems 2025-07-08 Michael Tang , Umar Javed , Xudong Chen , Miroslav Krstic , Jorge I. Poveda

We present a general framework for evolutionary learning to emergent unbiased state representation without any supervision. Evolutionary frameworks such as self-play converge to bad local optima in case of multi-agent reinforcement learning…

Machine Learning · Statistics 2023-02-03 Shohei Ohsawa