Mechanisms for information elicitation

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Mechanisms for information elicitation

We study the computational aspects of information elicitation mechanisms in which a principal attempts to elicit the private information of other agents using a carefully selected payment scheme based on proper scoring rules. Scoring rules, like many other mechanisms set in a probabilistic environment, assume that all participating agents share some common belief about the underlying probabilit...

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This paper further studies a model of information elicitation due to Smorodinsky and Tennenholtz [13], where the introduction of sequential mechanisms results in more efficiency than the classical simultaneous mechanism design approach entails. Whereas the original work focused on anonymous function and settings where information is distributed independently across agents we extend the results ...

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Information elicitation mechanisms, such as Peer Prediction [11] and Bayesian Truth Serum [12], are designed to reward agents for honestly reporting their private information, even when this information cannot be directly verified. Information elicitation mechanisms, such as these, are cleverly designed so that truth-telling is a strict Bayesian Nash Equilibrium. However, a key challenge that h...

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Proper scoring rules, particularly when used as the basis for a prediction market, are powerful tools for eliciting and aggregating beliefs about events such as the likely outcome of an election or sporting event. Such scoring rules incentivize a single agent to reveal her true beliefs about the event. Othman and Sandholm [16] introduced the idea of a decision rule to examine these problems in ...

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ژورنال

عنوان ژورنال: Artificial Intelligence

سال: 2008

ISSN: 0004-3702

DOI: 10.1016/j.artint.2008.08.005