计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 275-282.doi: 10.11896/jsjkx.210700129
傅彦铭1, 朱杰夫1, 蒋侃2, 黄保华1, 孟庆文1, 周兴1
FU Yan-ming1, ZHU Jie-fu1, JIANG Kan2, HUANG Bao-hua1, MENG Qing-wen1, ZHOU Xing1
摘要: 随着移动众包的快速发展,市面上的众包平台如雨后春笋般出现,它们发布任务并利用人群的力量来执行任务、收集数据。此时,移动众包中有效的激励机制变得十分重要。然而现有的激励机制只片面地考虑工人的信誉度、所在位置和执行时间等,这使得众包平台在有限的预算或其他约束的情况下选定优质工人并分配多个任务变得困难。针对以上问题,文中提出了一种基于多约束工人择优的激励机制(Multi-constrained Worker Selection Incentive Mechanism,MSIM),该模型依赖于两个相关算法:一是基于改进逆向拍卖的工人择优算法,该算法综合考虑工人信誉度、地理位置、任务完成度、结果质量等多个重要约束来选择最优的工人执行任务;二是评估和奖惩算法,该算法对任务执行结果和工人信誉度进行评估,从而制定对工人的奖励与惩罚规则。实验结果表明,MSIM可以选出优秀的工人,并提高任务执行结果的可信度和工人信誉度,是一种良好的激励机制。
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