Automated workflow synthesis

Haoqi Zhang, Eric Horvitz, David C. Parkes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013
Pages1020-1026
Number of pages7
StatePublished - Dec 1 2013
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: Jul 14 2013Jul 18 2013

Publication series

NameProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

Other

Other27th AAAI Conference on Artificial Intelligence, AAAI 2013
CountryUnited States
CityBellevue, WA
Period7/14/137/18/13

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Zhang, H., Horvitz, E., & Parkes, D. C. (2013). Automated workflow synthesis. In Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013 (pp. 1020-1026). (Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013).