A Quality Assuring Multi-armed Bandit Crowdsourcing Mechanism with Incentive Compatible Learning

被引：0
|
作者：
Jain, Shweta [1 ]
Gujar, Sujit [2 ]
Zoeter, Onno [3 ]
Narahari, Y. [1 ]
机构：
[1] IISc Bangalore, Bengaluru, India
[2] EPFL Lausanne, Lausanne, Switzerland
[3] XRCE Meylan, Meylan, France
来源：
AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS | 2014年
关键词：
Mechanism Design; Multi-armed Bandit; Crowdsourcing;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We develop a novel multi-armed bandit (MAB) mechanism for the problem of selecting a subset of crowd workers to achieve an assured accuracy for each binary labelling task in a cost optimal way. This problem is challenging because workers have unknown qualities and strategic costs.
引用
收藏
页码：1609 / 1610
页数：2
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