论文标题
噪声和波动会破坏小组评估问题多数规则的效率
Noise and fluctuations can undermine the efficiency of Majority Rule in Group Evaluation problems
论文作者
论文摘要
众包是一种通过共享想法，努力和资源来执行任务的机制。多亏了在线技术，在过去的十年中，众包在不同和多样化的领域中变得更加利用。这种过程的一个实例是所谓的“标签聚合问题”：实际上，这是代理人对项目的评估，每个代理都会在其中做出自己的判断。从成员的个人评估开始，小组如何进行全球评估？在这项工作中，通过游戏理论，进化的方法，我们表明，在大多数情况下，大多数规则（小组评估是对大多数成员的评估）仍然是获得可靠的小组评估的最佳方法，即使代理商并不是该主题的最佳专家；另一方面，我们还表明噪声（即，偶然的错误，误解或每个可能的非确定性结果来源）可能会破坏在非平凡情况下该程序的效率。因此，为了使过程尽可能可靠，应仔细考虑噪声及其影响的存在。
Crowdsourcing is a mechanism by means of which groups of people are able to execute a task by sharing ideas, efforts and resources. Thanks to the online technologies, crowdsourcing has become in the last decade an even more utilized process in different and diverse fields. An instance of such process is the so-called "label aggregation problem": in practice, it is the evaluation of an item by groups of agents, where each agent gives its own judgment of it. Starting from the individual evaluations of their members, how can the groups give their global assessment? In this work, by means of a game-theoretical, evolutionary approach, we show that in most cases the majority rule (the group evaluation is the evaluation of the majority of its members) is still the best way to get a reliable group evaluation, even when the agents are not the best experts of the topic at stake; on the other hand, we also show that noise (i.e., fortuitous errors, misunderstanding, or every possible source of non-deterministic outcomes) can undermine the efficiency of the procedure in non-trivial situations. Therefore, in order to make the process as reliable as possible, the presence of noise and its effects should be carefully taken into account.
