Automated Workflow Synthesis

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Automated Workflow Synthesis

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Title: Automated Workflow Synthesis
Author: Zhang, Haoqi; Horvitz, Eric; Parkes, David C.

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Citation: Zhang, Haoqi, Eric Horvitz, and David C. Parkes. 2013. Automated Workflow Synthesis. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), Bellevue, WA, July 14-18, 2013: 1020-1026.
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Abstract: By coordinating efforts from humans and machines, human computation systems can solve problems that machines cannot tackle alone. A general challenge is to design efficient human computation algorithms or workflows with which to coordinate the work of the crowd. We introduce a method for automated workflow synthesis aimed at ideally harnessing human efforts by learning about the crowd's performance on tasks and synthesizing an optimal workflow for solving a problem. We present experimental results for human sorting tasks, which demonstrate both the benefit of understanding and optimizing the structure of workflows based on observations. Results also demonstrate the benefits of using value of information to guide experiments for identifying efficient workflows with fewer experiments.
Published Version: http://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6457
Other Sources: http://research.microsoft.com/en-us/um/people/horvitz/workflow_synthesis-aaai_2013.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:30782202
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