一種面向眾包的基于信譽值的激勵機制

芮蘭蘭; 張攀; 黃豪球; 邱雪松

doi:10.11999/JEIT151095

一種面向眾包的基于信譽值的激勵機制

doi: 10.11999/JEIT151095

基金項目:

國家自然科學基金(61302078, 61372108)，國家自然科學基金創(chuàng)新研究群體科學基金(61121061)，北京高等學校青年英才計劃項目(YETP0476)

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- 文章訪問數(shù): 2226
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-09-25
- 修回日期: 2016-04-22
- 刊出日期: 2016-07-19

Reputation-based Incentive Mechanisms in Crowdsourcing

Funds:

The National Natural Science Foundation of China (61302078, 61372108), The Funds for Creative Research Groups of China (61121061), Beijing Higher Education Young Elite Teacher Project (YETP0476)

摘要

摘要: 眾包是互聯(lián)網帶來的一種分布式問題解決模式。然而，由于工作者和任務發(fā)布者具有自私特性并且致力于獲得自身效益的最大化，使得在眾包應用中，存在內部的激勵問題。該文主要完成以下工作：首先，基于重復博弈，提出一種基于信譽值的激勵模型，用于激勵理性工作者高質量地完成任務；其次，該激勵模型中同時設置了懲罰機制，將針對惡意工作者做出相應懲罰。仿真結果表明，即使在自私工作者比例為0.2的條件下，只要合理選擇懲罰參數(shù)，均可有效激勵理性工作者的盡力工作，眾包平臺的整體性能可以提升至90%以上。
- 眾包平臺 /
- 激勵模型 /
- 懲罰機制 /
- 重復博弈
Abstract: Crowdsourcing is a new distributed problem solving pattern brought by the Internet. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester are selfish and aim to maximize their own benefit. In this paper, the following key contributions are made. A reputation-based incentive model is designed using repeated game theory, based on thorough analysis for current research on reputation and incentive mechanism; and a punishment mechanism is established to counter selfish workers. The experiment results show that the new established model can efficiently motivate the rational workers and counter the selfish ones. By setting punishment parameters appropriately, the overall performance of crowdsourcing system can be improved up to 90%, even if the fraction of selfish workers is 20%.
- Crowdsourcing system /
- Incentive mechanisms /
- Punishment mechanisms /
- Repeated game

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參考文獻(20)

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