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Game Theory for Data Science: Eliciting Truthful Information

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Intelligent systems often depend on data provided by information agents, for example, sensor data or crowdsourced human computation. Providing accurate and relevant data requires costly effort that agents may not always be willing to provide. Thus, it becomes important not only to verify the correctness of data, but also to provide incentives so that agents that provide high-quality data are rewarded while those that do not are discouraged by low rewards. We cover different settings and the assumptions they admit, ...

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Game Theory for Data Science: Eliciting Truthful Information
2017, Morgan & Claypool, San Rafael

ISBN-13: 9781627057295

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