Optimal Posted-Price Mechanism in Microtask Crowdsourcing

Optimal Posted-Price Mechanism in Microtask Crowdsourcing

Zehong Hu, Jie Zhang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 228-234. https://doi.org/10.24963/ijcai.2017/33

Posted-price mechanisms are widely-adopted to decide the price of tasks in popular microtask crowdsourcing. In this paper, we propose a novel posted-price mechanism which not only outperforms existing mechanisms on performance but also avoids their need of a finite price range. The advantages are achieved by converting the pricing problem into a multi-armed bandit problem and designing an optimal algorithm to exploit the unique features of microtask crowdsourcing. We theoretically show the optimality of our algorithm and prove that the performance upper bound can be achieved without the need of a prior price range. We also conduct extensive experiments using real price data to verify the advantages and practicability of our mechanism.
Keywords:
Agent-based and Multi-agent Systems: Economic paradigms, auctions and market-based systems
Multidisciplinary Topics and Applications: AI and Social Sciences