dc.contributor.author | Azar, Pablo Daniel | |
dc.contributor.author | Micali, Silvio | |
dc.date.accessioned | 2020-09-02T22:59:50Z | |
dc.date.available | 2020-09-02T22:59:50Z | |
dc.date.issued | 2018-05 | |
dc.date.submitted | 2017-08 | |
dc.identifier.issn | 1555-7561 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/126895 | |
dc.description.abstract | Collecting and processing large amounts of data is becoming increasingly crucial in our society. We model this task as evaluating a function f over a large vector x=(x1,…,xn), which is unknown, but drawn from a publicly known distribution X. In our model, learning each component of the input x is costly, but computing the output f(x) has zero cost once x is known. We consider the problem of a principal who wishes to delegate the evaluation of f to an agent whose cost of learning any number of components of x is always lower than the corresponding cost of the principal. We prove that, for every continuous function f and every ϵ>0, the principal can—by learning a single component xi of x—incentivize the agent to report the correct value f(x) with accuracy ϵ. complexity. Copyright ©2018 The Authors. | en_US |
dc.description.sponsorship | Robert Solow Fellowship | en_US |
dc.description.sponsorship | Stanley and Rhoda Fischer Fellowship | en_US |
dc.language.iso | en | |
dc.publisher | The Econometric Society | en_US |
dc.relation.isversionof | https://dx.doi.org/10.3982/TE1815 | en_US |
dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs License | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | en_US |
dc.source | Wiley | en_US |
dc.title | Computational principal-agent problems | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Azar, Pablo D. and Silvio Micali, "Computational principal–agent problems." Theoretical Economics 13, 2 (May 2018): p. 553-78 doi. 10.3982/TE1815 ©2018 Authors | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Economics | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.relation.journal | Theoretical Economics | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2019-06-14T18:19:09Z | |
dspace.date.submission | 2019-06-14T18:19:10Z | |
mit.journal.volume | 13 | en_US |
mit.journal.issue | 2 | en_US |
mit.metadata.status | Complete | |