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Related papers: Strategy-Proof Incentives for Predictions

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Prediction markets aggregate agents' beliefs regarding a future event, where each agent is paid based on the accuracy of its reported belief when compared to the realized outcome. Agents may strategically manipulate the market (e.g., delay…

Computer Science and Game Theory · Computer Science 2012-12-27 Ayman Ghoneim , Robert C. Williamson

Proper scoring rules elicit truth-telling when making predictions, or otherwise revealing information. However, when multiple predictions are made of the same event, telling the truth is in general no longer optimal, as agents are motivated…

Computer Science and Game Theory · Computer Science 2017-07-04 Amir Ban

Peer prediction mechanisms incentivize agents to truthfully report their signals even in the absence of verification by comparing agents' reports with those of their peers. In the detail-free multi-task setting, agents respond to multiple…

Computer Science and Game Theory · Computer Science 2021-08-27 Grant Schoenebeck , Fang-Yi Yu

Enhancing resilience in multi-agent systems in the face of selfish agents is an important problem that requires further characterisation. This work develops a truthful mechanism that avoids self-interested and strategic agents maliciously…

Systems and Control · Electrical Eng. & Systems 2025-07-29 Tianyi Zhong , David Angeli

Strategy-proof mechanisms are widely used in market design. In an abstract allocation framework where outside options are available to agents, we obtain two results for strategy-proof mechanisms. They provide a unified foundation for…

Theoretical Economics · Economics 2021-01-05 Jun Zhang

When eliciting forecasts from a group of experts, it is important to reward predictions so that market participants are incentivized to tell the truth. Existing mechanisms partially accomplish this but remain susceptible to groups of…

Theoretical Economics · Economics 2024-11-26 Jack Edwards

Auctions in which agents' payoffs are random variables have received increased attention in recent years. In particular, recent work in algorithmic mechanism design has produced mechanisms employing internal randomization, partly in…

Computer Science and Game Theory · Computer Science 2012-06-15 Shaddin Dughmi , Yuval Peres

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a…

Computer Science and Game Theory · Computer Science 2014-01-16 Radu Jurca , Boi Faltings

In many predictive decision-making scenarios, such as credit scoring and academic testing, a decision-maker must construct a model that accounts for agents' propensity to "game" the decision rule by changing their features so as to receive…

Machine Learning · Computer Science 2022-08-26 Yonadav Shavit , Benjamin Edelman , Brian Axelrod

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness; it is not incorporated in players' utility functions (and doing so…

Computer Science and Game Theory · Computer Science 2012-11-14 Yiling Chen , Stephen Chong , Ian A. Kash , Tal Moran , Salil Vadhan

It is typically expected that if a mechanism is truthful, then the agents would, indeed, truthfully report their private information. But why would an agent believe that the mechanism is truthful? We wish to design truthful mechanisms,…

Computer Science and Game Theory · Computer Science 2014-12-02 Simina Brânzei , Ariel D. Procaccia

Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budget-balance, stability against deviations by…

Computer Science and Game Theory · Computer Science 2012-05-14 Benjamin Lubin , David C. Parkes

Obviously strategyproof (OSP) mechanisms maintain the incentive compatibility of agents that are not fully rational. They have been object of a number of studies since their recent definition. A research agenda, initiated in…

Computer Science and Game Theory · Computer Science 2018-04-30 Diodato Ferraioli , Carmine Ventre

We revisit the problem of designing strategyproof mechanisms for allocating divisible items among two agents who have linear utilities, where payments are disallowed and there is no prior information on the agents' preferences. The…

Computer Science and Game Theory · Computer Science 2017-04-13 Yun Kuen Cheung

In many societal resource allocation domains, machine learning methods are increasingly used to either score or rank agents in order to decide which ones should receive either resources (e.g., homeless services) or scrutiny (e.g., child…

Multiagent Systems · Computer Science 2020-12-17 Andrew Estornell , Sanmay Das , Yevgeniy Vorobeychik

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

We consider the problem of conducting a survey with the goal of obtaining an unbiased estimator of some population statistic when individuals have unknown costs (drawn from a known prior) for participating in the survey. Individuals must be…

Computer Science and Game Theory · Computer Science 2012-03-05 Aaron Roth , Grant Schoenebeck

Mechanism design is addressed in the context of fair allocations of indivisible goods with monetary compensation. Motivated by a real-world social choice problem, mechanisms with verification are considered in a setting where (i) agents'…

Computer Science and Game Theory · Computer Science 2012-09-18 Gianluigi Greco , Francesco Scarcello

Algorithms are often used to produce decision-making rules that classify or evaluate individuals. When these individuals have incentives to be classified a certain way, they may behave strategically to influence their outcomes. We develop a…

Machine Learning · Computer Science 2019-08-02 Jon Kleinberg , Manish Raghavan

Prediction markets provide an efficient means to assess uncertain quantities from forecasters. Traditional and competitive strictly proper scoring rules have been shown to incentivize players to provide truthful probabilistic forecasts.…

Computer Science and Game Theory · Computer Science 2012-02-20 SangIn Chun , Ross D. Shachter
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