EAGER: Dynamics of collaboration between humans and engineered systems: system design for collective expertise

EAGER：人类与工程系统之间的协作动态：集体专业知识的系统设计

• 批准号: 1547864
• 负责人: Maurizio Porfiri
• 金额: $ 30万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547864&HistoricalAwards=false
• 关键词: EAGER; Dynamics; collaboration; between; humans

1547864(Porfiri)Humans are being continuously involved as cognitive and social agents in engineered systems, and, in a similar vein, engineered systems are becoming increasingly integral to systems of interacting humans. A particularly elusive issue entails understanding and predicting the evolution of the collaboration between humans and engineered systems, across behavioral and technological domains. This award supports experimental and theoretical research to elucidate the dynamics of collaboration in human-engineered systems, through the integration of dynamical systems theory, robotics, and human-computer interactions. Humans will socially interact with engineered systems in an engineering context, which will be, in turn, enabled by an engineering infrastructure. This research will contribute to lay the foundation for the next generation of autonomous environmental monitoring systems, which capitalize on human intelligence and low-cost distributed robots for rapidly and accurately monitoring the environment. Complementing the research are interdisciplinary formal and informal education activities that will benefit the training of underprivileged students and reach out to economically-disadvantaged local communities.This research program seeks to establish a transformative experimental and theoretical framework for understanding, predicting, and, ultimately, controlling the evolution of the collaboration between humans and engineered systems. In a novel crowdsourcing infrastructure, online groups comprised of real humans and artificial experts will collaboratively perform aquatic environmental monitoring, by virtually patrolling mobile aquatic robots in a polluted canal in Brooklyn, NY, to explore the water basin, collect and classify wildlife images, and identify sources of pollution. Similar to a mechanics experiment in which one applies a sequence of mechanical forces to a solid and measures its mechanical deformation, this project will study the response of humans to the controlled actions of artificial experts and investigate their intertwined dynamics, in terms of social interactions and task performance. A series of hypothesis-driven studies will explore the roles of human cognitive abilities, dispositional factors, and behavioral plasticity on technology-mediated social interactions and performance. A new data-driven mathematical framework based on signal processing, network science, and information theory will be formulated to uncover the interplay between personal attributes and plasticity of humans, their interactions with engineered systems, and how to better design a human-engineered system for collective expertise.

1547864（Porfiri）人类一直在工程系统中不断成为认知和社会代理人，并且在类似的静脉里，工程系统变得越来越成为互动人类系统的组成部分。一个特别难以捉摸的问题需要理解和预测人类与工程系统之间在行为和技术领域之间的协作的演变。该奖项支持实验和理论研究，以通过动态系统理论，机器人技术和人类计算机相互作用的整合来阐明人类工程系统中协作的动态。人类将在工程环境中与工程系统进行社交，这将由工程基础架构启用。这项研究将有助于为下一代自动环境监测系统奠定基础，该系统利用了人类智能和低成本分布式机器人，以快速，准确地监测环境。 补充这项研究是跨学科的正规和非正式教育活动，这些活动将有益于贫困学生的培训并接触经济待遇的当地社区。本研究计划旨在建立一个变革性的实验和理论框架，以理解，预测，并最终控制人类和工程系统之间的协作演化。在一个新颖的众包基础设施中，由真正的人类和人造专家组成的在线团体将通过在纽约州布鲁克林市的一条污染运河中巡逻移动水上机器人进行协作进行水生环境监测，以探索水池，收集和分类野生动物图像，并确定污染的来源。 与机械实验类似，在该实验中，人们将一系列力学应用于固体并衡量其机械变形，该项目将研究人类对人工专家的受控作用的反应，并在社交互动和任务绩效方面研究其相互交织的动态。一系列假设驱动的研究将探讨人类认知能力，性格因素以及行为可塑性对技术介导的社会互动和表现的作用。将制定基于信号处理，网络科学和信息理论的新的数据驱动的数学框架，以揭示人类的个人属性和可塑性之间的相互作用，与工程系统的相互作用，以及如何更好地设计人类工程化的系统以进行集体专业知识。

项目成果

The Influence of Social Information and Self-expertise on Emergent Task Allocation in Virtual Groups

社会信息和自我专业知识对虚拟群体紧急任务分配的影响

• DOI: 10.3389/fevo.2018.00016
• 发表时间: 2018
• 期刊: Frontiers in Ecology and Evolution
• 影响因子: 3
• 作者: Nakayama, Shinnosuke;Diner, David;Holland, Jacob G.;Bloch, Guy;Porfiri, Maurizio;Nov, Oded
• 通讯作者: Nov, Oded

Topological features determining the error in the inference of networks using transfer entropy

使用传递熵确定网络推理误差的拓扑特征

• DOI: 10.3934/mine.2020003
• 发表时间: 2020
• 期刊: Mathematics in Engineering
• 影响因子: 1
• 作者: H. Goodman, Roy;Porfiri, Maurizio
• 通讯作者: Porfiri, Maurizio

Transfer entropy on symbolic recurrences

符号递归的传递熵

• DOI: 10.1063/1.5094900
• 发表时间: 2019
• 期刊: Chaos: An Interdisciplinary Journal of Nonlinear Science
• 作者: Porfiri, Maurizio;Ruiz Marín, Manuel
• 通讯作者: Ruiz Marín, Manuel

Producing knowledge by admitting ignorance: Enhancing data quality through an “I don’t know” option in citizen science

通过承认无知来生产知识：通过公民科学中的“我不知道”选项来提高数据质量

• DOI: 10.1371/journal.pone.0211907
• 发表时间: 2019
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Torre, Marina;Nakayama, Shinnosuke;Tolbert, Tyrone J.;Porfiri, Maurizio;Kestler, Hans A.
• 通讯作者: Kestler, Hans A.

Bring them aboard: Rewarding participation in technology-mediated citizen science projects

• DOI: 10.1016/j.chb.2018.08.017
• 发表时间: 2018-12-01
• 期刊: COMPUTERS IN HUMAN BEHAVIOR
• 影响因子: 9.9
• 作者: Cappa, Francesco;Laut, Jeffrey;Giustiniano, Luca
• 通讯作者: Giustiniano, Luca