Efficient task sub-delegation for crowdsourcing

摘要: Reputation-based approaches allow a crowdsourcing system to identify reliable workers whom tasks can be delegated. In systems that modeled as multi-agent trust networks consist of resource constrained trustee agents (i.e., workers), may need further sub-delegate others if they determine cannot complete all pending before the stipulated deadlines. Existing reputation-based decision-making models help decide when and tasks. this paper, we proposed reputation aware task sub-delegation (RTS) approach bridge gap. By jointly considering worker's reputation, workload, price its effort relationships with others, RTS implemented an intelligent agent make decisions in distributed manner. The resulting allocation maximizes social welfare through efficient utilization collective capacity crowd, provides provable performance guarantees. Experimental comparisons state-of-the-art based on Epinions network demonstrate significant advantages under high workload conditions.