A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms

2014-11-05

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2

Volume

Vol. 2 (2014): Second AAAI Conference on Human Computation and Crowdsourcing

Works in Progress

Task starvation leads to huge variation in the completion times of the tasks posted on to the crowd. The price offered to a given task together with the dynamics of the crowd at the time of posting affect its completion time. Large organizations/requesters who frequent the crowd at regular intervals in order to get their tasks done desire predictability in completion times of the tasks. Thus, such requesters have to take into account the crowd dynamics at the time of posting the tasks and price them accordingly. In this work, we study an instance of the pricing problem and propose a solution based on the framework of Markov Decision Processes (MDPs).

10.1609/hcomp.v2i1.13183