Decision-Theoretic Control of Crowd-Sourced Workflows

摘要

Systems and methods for the decision-theoretic control and optimization of crowd-sources workflows utilize a computing device to map a workflow to complete a directive. The directive includes a utility function, and the workflow comprises an ordered task set. Decision points precede and follow each task in the task set, and each decision point may require (a) posting a call for workers to complete instances of tasks in the task set; (b) adjusting parameters of tasks in the task set; or (c) submitting an artifact generated by a worker as output. The computing device accesses a plurality of workers having capability parameters that describe the workers' respective abilities to complete tasks. The computing device implements the workflow by optimizing and/or selecting user-preferred choices at decision points according to the utility function and submits an artifact as output. The computing device may also implement a training phase to ascertain worker capability parameters.