@article{Yu_Miao_Shen_Leung_Chen_Yang_2015, title={Efficient Task Sub-Delegation for Crowdsourcing}, volume={29}, url={https://ojs.aaai.org/index.php/AAAI/article/view/9337}, DOI={10.1609/aaai.v29i1.9337}, abstractNote={ <p> Reputation-based approaches allow a crowdsourcing system to identify reliable workers to whom tasks can be delegated. In crowdsourcing systems that can be modeled as multi-agent trust networks consist of resource constrained trustee agents (i.e., workers), workers may need to further sub-delegate tasks to others if they determine that they cannot complete all pending tasks before the stipulated deadlines. Existing reputation-based decision-making models cannot help workers decide when and to whom to sub-delegate tasks. In this paper, we proposed a reputation aware task sub-delegation (RTS) approach to bridge this gap. By jointly considering a worker’s reputation, workload, the price of its effort and its trust relationships with others, RTS can be implemented as an intelligent agent to help workers make sub-delegation decisions in a distributed manner. The resulting task allocation maximizes social welfare through efficient utilization of the collective capacity of a crowd, and provides provable performance guarantees. Experimental comparisons with state-of-the-art approaches based on the Epinions trust network demonstrate significant advantages of RTS under high workload conditions. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Yu, Han and Miao, Chunyan and Shen, Zhiqi and Leung, Cyril and Chen, Yiqiang and Yang, Qiang}, year={2015}, month={Feb.} }