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dc.contributor.author	Chen, Yiling
dc.contributor.author	Bacon, David F.
dc.contributor.author	Kash, Ian
dc.contributor.author	Parkes, David C.
dc.contributor.author	Rao, Malvika
dc.contributor.author	Sridharan, Manu
dc.date.accessioned	2012-02-21T15:46:19Z
dc.date.issued	2012
dc.identifier.citation	Bacon, David F., Yiling Chen, Ian Kash, David C. Parkes, Malvika Rao, and Manu Sridharan. Forthcoming. Predicting your own effort. In Proceedings of the 11th International Conference on Autonomous and Multiagent Systems (AAMAS 2012), June 4–8, 2012, Valencia, Spain, eds. Conitzer, Winikoff, Padgham, and van der Hoek.	en_US
dc.identifier.uri	http://nrs.harvard.edu/urn-3:HUL.InstRepos:8191221
dc.description.abstract	We consider a setting in which a worker and a manager may each have information about the likely completion time of a task, and the worker also affects the completion time by choosing a level of effort. The task itself may further be composed of a set of subtasks, and the worker can also decide how many of these subtasks to split out into an explicit prediction task. In addition, a worker can learn about the likely completion time of a task as work on subtasks completes. We characterize a family of scoring rules for the worker and manager such that information is truthfully reported, best effort is exerted by the worker in completing tasks as quickly as possible, and collusion is not possible. We study the factors influencing when a worker will split a task into subtasks, each forming a separate prediction target.	en_US
dc.description.sponsorship	Engineering and Applied Sciences	en_US
dc.language.iso	en_US	en_US
dc.publisher	International Foundation for Autonomous Agents and Multiagent Systems	en_US
dash.license	OAP
dc.title	Predicting Your Own Effort	en_US
dc.type	Journal Article	en_US
dc.description.version	Accepted Manuscript	en_US
dc.relation.journal	Proceedings of the 11th International Conference on Autonomous and Multiagent Systems (AAMAS 2012)	en_US
dash.depositing.author	Chen, Yiling
dc.date.available	2012-02-21T15:46:19Z

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  Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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