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众包物理学：用于物理任务的计划性和机会性众包

Crowdphysics: Planned and Opportunistic Crowdsourcing for Physical Tasks
课程网址: https://videolectures.net/videos/icwsm2013_sadilek_physical_tasks  
主讲教师: Adam Sadilek
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2014-04-03
课程语种: 英语
中文简介:
关于人工计算和众包的研究集中在可以通过 Internet 远程完成的任务上。我们介绍了一类我们称为众包物理学 （CP）---众包任务的一般问题，这些问题需要人们在时间和物理空间上进行协作和同步。举个说明性示例，我们重点介绍一种众筹驱动的配送服务 ---一种特定的 CP 实例，人们可以在其中进行日常生活，但有机会携带包裹以运送到特定地点或个人。每个包裹都根据时间和空间的重叠在人与人之间传递，直到交付。我们通过简化为图形规划问题来制定 CP 任务，并使用大量地理标记推文样本作为人们位置的代理来分析性能。我们表明，包裹可以以非凡的速度和覆盖范围交付。当我们知道人们的未来位置时，以及在没有全球知识的情况下进行路由，只做出本地贪婪决策时，这些结果都适用。据我们所知，这是第一个实证证明移动个人的动态网络是高度可导航的。
课程简介: Research on human computation and crowdsourcing has concentrated on tasks that can be accomplished remotely over the Internet. We introduce a general class of problems we call crowdphysics (CP)---crowdsourcing tasks that require people to collaborate and synchronize both in time and physical space. As an illustrative example, we focus on a crowd-powered delivery service---a specific CP instance where people go about their daily lives, but have the opportunity to carry packages to be delivered to specific locations or individuals. Each package is handed off from person to person based on overlaps in time and space until it is delivered. We formulate CP tasks by reduction to a graph-planning problem, and analyze the performance using a large sample of geotagged tweets as a proxy for people's location. We show that packages can be delivered with remarkable speed and coverage. These results hold for the case when we know people's future locations and also when routing without global knowledge, making only local greedy decisions. To our knowledge, this is the first empirical evidence that dynamic networks of mobile individuals are highly navigable.
关 键 词: 众包物理学; 众筹配送服务; 动态网络导航
课程来源: videolectures
数据采集: 2025-05-16：yuhongrui
最后编审: 2025-05-16：yuhongrui
阅读次数: 2

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