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Optimally aggregating elicited expertise : a proposed application of the Bayesian Truth Serum for policy analysis

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dc.contributor.advisor Drazen Prelec. en_US
dc.contributor.author Weiss, Rebecca (Rebecca Jennifer) en_US
dc.contributor.other Massachusetts Institute of Technology. Technology and Policy Program. en_US
dc.date.accessioned 2010-03-25T14:55:51Z
dc.date.available 2010-03-25T14:55:51Z
dc.date.copyright 2009 en_US
dc.date.issued 2009 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/53066
dc.description Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2009. en_US
dc.description Includes bibliographical references (p. 59-63). en_US
dc.description.abstract Uncertainty and risk are obstacles that nearly all policy-makers encounter during their careers. However, evaluating uncertainty and risk can be difficult since these concepts may be broadly defined. This may result in inaccurate estimates of risk and uncertainty. Expert elicitation is a formal, structured method of obtaining subjective expert judgment in scenarios where objective data is unobtainable. It is designed to reduce the influence of ambiguity on expert judgment, meaning that analysts may use such subjective data as if it were objectively generated. Expert elicitation methods tend to aggregate expert judgment in order to create a unified response, but determining how to combine expert opinions remains a difficult problem. In this thesis, a review of the literature and background behind defining expertise and expert elicitation will be provided. Additionally, this thesis introduces the Bayesian Truth Serum as a potential weighting algorithm for combining expert judgments. As opposed to other weighting algorithms, the Bayesian Truth Serum uses the metaknowledge of experts to create weights for aggregation. Using such information may prove superior to assuming a normal distribution of expertise or relying upon experts to provide estimates of their own expertise. en_US
dc.description.statementofresponsibility by Rebecca Weiss. en_US
dc.format.extent 63 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Engineering Systems Division. en_US
dc.subject Technology and Policy Program. en_US
dc.title Optimally aggregating elicited expertise : a proposed application of the Bayesian Truth Serum for policy analysis en_US
dc.title.alternative Proposed application of the Bayesian Truth Serum for policy analysis en_US
dc.type Thesis en_US
dc.description.degree S.M.in Technology and Policy en_US
dc.contributor.department Massachusetts Institute of Technology. Engineering Systems Division. en_US
dc.contributor.department Massachusetts Institute of Technology. Technology and Policy Program. en_US
dc.identifier.oclc 501829428 en_US


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