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Challenges of human–machine collaboration in risky decision-making

《工程管理前沿（英文）》 2022年第9卷第1期页码 89-103 doi: 10.1007/s42524-021-0182-0

摘要： The purpose of this paper is to delineate the research challenges of human–machine collaboration in risky decision-making. Technological advances in machine intelligence have enabled a growing number of applications in human–machine collaborative decision-making. Therefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilities. In risky decision-making, a human decision-maker is vulnerable to cognitive biases when judging the possible outcomes of a risky event, whereas a machine decision-maker cannot handle new and dynamic contexts with incomplete information well. We first summarize features of risky decision-making and possible biases of human decision-makers therein. Then, we argue the necessity and urgency of advancing human–machine collaboration in risky decision-making. Afterward, we review the literature on human–machine collaboration in a general decision context, from the perspectives of human–machine organization, relationship, and collaboration. Lastly, we propose challenges of enhancing human–machine communication and teamwork in risky decision-making, followed by future research avenues.

关键词： human–machine collaboration risky decision-making human–machine team and interaction task allocation human–machine relationship

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The imperative need to develop guidelines to manage human versus machine intelligence

Donald KENNEDY, Simon P. PHILBIN

《工程管理前沿（英文）》 2018年第5卷第2期页码 182-194 doi: 10.15302/J-FEM-2018085

摘要： Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions. Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area.

关键词： human intelligence & machine intelligence HI-MI decision-making artificial intelligence

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基于人体髋关节转动中心分析的髋关节外骨骼仿生设计 Article

Wei YANG,Can-jun YANG,Ting XU

《信息与电子工程前沿（英文）》 2016年第17卷第8期页码 792-802 doi: 10.1631/FITEE.1500286

摘要：为了改善外骨骼穿戴舒适性，本文提出了一种基于人机物理交互优化的外骨骼设计方法。该方法通过设计外骨骼髋关节，使其保证人体髋关节运动时外骨骼髋关节转动中心能跟随人体髋关节转动中心的运动轨迹。当人体髋关节运动时，通过实验测量和计算可以得到其转动中心轨迹。本文设计的外骨骼髋关节运动机构能在人体髋关节屈曲/伸展和外展/内收时，保证转动中心都能够包容人体髋关节转动中心运动范围。同时，所设计的外骨骼髋关节被应用到下肢步行康复训练外骨骼中。通过人机接触力实验可知，与传统设计外骨骼髋关节进行相比，本文设计的仿生髋关节外骨骼在髋关节屈曲/伸展和内收/外展时分别可以减小24.1%和76.0%的人机接触力。这一结果证明仿生设计髋关节外骨骼更具穿戴舒适性，更符合人机工程学的设计要求。最后，本文通过建立人机闭式链模型进一步分析了仿生设计对于人体髋关节内力的影响，并验证该设计能减少关节内力作用。

关键词：髋关节外骨骼；髋关节中心；柔顺关节；人机交互力

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Machine learning-based seismic assessment of framed structures with soil-structure interaction

《结构与土木工程前沿（英文）》 2023年第17卷第2期页码 205-223 doi: 10.1007/s11709-022-0909-y

摘要： The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.

关键词： seismic hazard artificial neural network soil-structure interaction seismic analysis

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平行认知：面向人机交互与管理的混合智能 Research Article

叶佩军1,王晓1,2,郑文博3,魏庆来1,4,王飞跃1,2,4

《信息与电子工程前沿（英文）》 2022年第23卷第12期页码 1765-1779 doi: 10.1631/FITEE.2100335

摘要：作为一门交叉学科，传统的认知科学主要采用实验、归纳、建模和验证的研究范式。对于包含大量用户异质行为和动态特性的社会物理信息系统，此种建模方法有时并不适用。为减少复杂人机系统中的人–机决策冲突，提出采用智能技术与系统来考察认知活动和认知功能的建模范式——平行认知。该范式分为三个阶段：基于人工认知系统的描述认知、基于计算思维实验的预测认知以及基于行为交互引导的引导性认知。在此基础上，进一步提出由心理模型和用户行为数据混合驱动的学习方法，自适应地学习人类个体的认知决策知识，从而使得三个阶段能够持续在线迭代。在交通行为引导和视觉推理场景下的初步实验表明，平行认知学习对于人类的行为引导是可行且有效的，有利于提升复杂工程系统和复杂社会系统中的人机协同程度。

关键词：认知学习；人工智能；行为引导

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The Group Interaction Field for Learning and Explaining Pedestrian Anticipation

Xueyang Wang,Xuecheng Chen,Puhua Jiang,Haozhe Lin,Xiaoyun Yuan,Mengqi Ji,Yuchen Guo,Ruqi Huang,Lu Fang,

《工程（英文）》 doi: 10.1016/j.eng.2023.05.020

摘要： Anticipating others’ actions is innate and essential in order for humans to navigate and interact well with others in dense crowds. This ability is urgently required for unmanned systems such as service robots and self-driving cars. However, existing solutions struggle to predict pedestrian anticipation accurately, because the influence of group-related social behaviors has not been well considered. While group relationships and group interactions are ubiquitous and significantly influence pedestrian anticipation, their influence is diverse and subtle, making it difficult to explicitly quantify. Here, we propose the group interaction field (GIF), a novel group-aware representation that quantifies pedestrian anticipation into a probability field of pedestrians’ future locations and attention orientations. An end-to-end neural network, GIFNet, is tailored to estimate the GIF from explicit multidimensional observations. GIFNet quantifies the influence of group behaviors by formulating a group interaction graph with propagation and graph attention that is adaptive to the group size and dynamic interaction states. The experimental results show that the GIF effectively represents the change in pedestrians’ anticipation under the prominent impact of group behaviors and accurately predicts pedestrians’ future states. Moreover, the GIF contributes to explaining various predictions of pedestrians’ behavior in different social states. The proposed GIF will eventually be able to allow unmanned systems to work in a human-like manner and comply with social norms, thereby promoting harmonious human–machine relationships.

关键词： Human behavior modeling and prediction Implicit representation of pedestrian anticipation Group interaction Graph neural network

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一种应用于功率放大液压驱动外骨骼的基于物理人机交互估计的控制策略 None

Yi LONG, Zhi-jiang DU, Wei-dong WANG, Long HE, Xi-wang MAO, Wei DONG

《信息与电子工程前沿（英文）》 2018年第19卷第9期页码 1076-1085 doi: 10.1631/FITEE.1601667

摘要：提出安装在外骨骼上的力矩传感器直接获得物理人机交互（physical human-robot interaction，pHRI）力矩信息。

关键词：外骨骼；物理人机交互；力矩传感器；人体步态；卡尔曼平滑器

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Development trend of urban design in “digital age”: Pan-dimensionality and individual-ubiquity

《结构与土木工程前沿（英文）》 2021年第15卷第3期页码 569-575 doi: 10.1007/s11709-021-0735-7

摘要： The wave of “digital age” featuring digital information is coming. Digital technology is profoundly changing the societal development direction and evolution paths. It also has significant bearing on production modes, social interactions and lifestyles. With regard to urban design, a system of knowledge about the creation and adaptation of material space forms that integrate humanities, art, technology and materials, digital technology has provided it with a brand-new and revolutionary scientific impetus for its evolution. The result of this evolution is “digital urban design paradigm based on human-computer interaction”, i.e., the urban development is moving toward “pan-dimensionality” and “individual ubiquity”. The future of urban design will construct a new approach to urban research and engineering, which is more complex, capable of accommodating and compatible with multiple goals of “instrumental rationality” and “value rationality”. Such a new approach shall be led by the probabilistic theory of “gray scale thinking”, reflecting quaternary synergetic view of “scientific rationality, ecological rationality, cultural rationality and technical rationality” to realize the cognitive progress of “engineering for the benefit of mankind”.

关键词： digital age urban design multiple objectives human-computer interaction pan-dimensionality individual-ubiquity

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Modeling and simulating the impact of forgetting and communication errors on delays in civil infrastructure shutdowns

Zhe SUN, Cheng ZHANG, Pingbo TANG

《工程管理前沿（英文）》 2021年第8卷第1期页码 109-121 doi: 10.1007/s42524-019-0084-6

摘要： Handoff processes during civil infrastructure operations are transitions between sequential tasks. Typical handoffs constantly involve cognitive and communication activities among operations personnel, as well as traveling activities. Large civil infrastructures, such as nuclear power plants (NPPs), provide critical services to modern cities but require regular or unexpected shutdowns (i.e., outage) for maintenance. Handoffs during such an outage contain interwoven workflows and communication activities that pose challenges to the cognitive and communication skills of handoff participants and constantly result in delays. Traveling time and changing field conditions bring additional challenges to effective coordination among multiple groups of people. Historical NPP records studied in this research indicate that even meticulous planning that takes six months before each outage could hardly guarantee sufficient back-up plans for handling various unexpected events. Consequently, delays frequently occur in NPP outages and bring significant socioeconomic losses. A synthesis of previous studies on the delay analysis of accelerated maintenance schedules revealed the importance and challenges of handoff modeling. However, existing schedule representation methods could hardly represent the interwoven communication, cognitive, traveling, and working processes of multiple participants collaborating on completing scheduled tasks. Moreover, the lack of formal models that capture how cognitive, waiting, traveling, and communication issues affect outage workflows force managers to rely on personal experiences in diagnosing delays and coordinating multiple teams involved in outages. This study aims to establish formal models through agent-based simulation to support the analytical assessment of outage schedules with full consideration of cognitive and communication factors involved in handoffs within the NPP outage workflows. Simulation results indicate that the proposed handoff modeling can help predict the impact of cognitive and communication issues on delays propagating throughout outage schedules. Moreover, various activities are fully considered, including traveling between workspaces and waiting. Such delay prediction capability paves the path toward predictive and resilience outage control of NPPs.

关键词： NPP outage human error team cognition handoff modeling

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人工智能与统计分析 Perspective

Bin YU, Karl KUMBIER

《信息与电子工程前沿（英文）》 2018年第19卷第1期页码 6-9 doi: 10.1631/FITEE.1700813

摘要：人工智能（artificial intelligence, AI）本质上是由数据驱动的。在其通过人机协作完成数据生成、算法开发与结果评估的任务中，需要应用许多统计概念。本文讨论了如何通过数据产生、兴趣问题探究、训练数据代表性和对结果审视等环节（Population, Question of interest, Representativeness of training data, Scrutiny of results, PQRS）来解决人机协作的问题。PQRS的工作流程为融合统计分析的思想与人类输入提供了一个概念框架。这些统计分析的思想包括通过随机化、局部控制以及稳定性的原则来获得算法和结果的可重复性与可解释性。我们讨论了这些原则在自动驾驶、自动医疗以及作者其他合作研究中的应用。

关键词：人工智能；统计；人机协作

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气球机器人在室内环境下与人的自然交互 None

Ning-shi YAO, Qiu-yang TAO, Wei-yu LIU, Zhen LIU, Ye TIAN, Pei-yu WANG, Timothy LI, Fumin ZHANG

《信息与电子工程前沿（英文）》 2019年第20卷第1期页码 45-59 doi: 10.1631/FITEE.1800587

摘要：为支持室内环境下长达两小时及以上的人机交互实验，我们研发了一款“佐治亚理工全自动迷你气球飞行机器人”（GT-MAB）。GT-MAB可以安全地与人近距离互动。该机器人具有人脸识别、自动跟踪人类使用者以及手势识别等功能。采用深度人工神经网络检测GT-MAB实时视频信号中人类使用者的脸和手，并基于此功能，设计一套人机交互系统实现GT-MAB与使用者之间的自然交互。GT-MAB的学习算法可以自主识别两种手势，因此在交互过程中，使用者无需佩戴任何装置就可与GT-MAB互动。基于机器视觉的反馈控制器可控制GT-MAB自动追踪并跟随使用者。一旦机器人成功识别使用者的手势，机器人会以对应的飞行轨迹回应使用者手势，同时将识别结果以及意图通过其自身搭载的LED显示屏展示给使用者。实验数据表明，向人类使用者展示的视觉信号能明显提高人类使用者和GT-MAB之间的交互体验。实验结果表明，GT-MAB作为一款新型飞行机器人，可在室内环境下安全地与人互动并有效采集人机交互数据。

关键词：气球机器人；人机交互；深度学习；人脸识别；手势识别

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基于双光源的实时视线追踪系统

黄莹,王志良,戚颖

《中国工程科学》 2008年第10卷第2期页码 86-90

摘要：

介绍了一个非穿戴式的低成本视线追踪系统。采用双近红外光源照射，单CCD相机获取信息的系统结构。并采用独特的双眼参数综合利用的方法来获取视线方向参数，使视线方向追踪效果更加稳定，并且同时扩大了有效追踪范围。此外，在视线方向参数获取、分析的过程中采用了一套快速算法使系统能满足实时性的要求。应用实例表明，该系统在人-机交互领域的应用已有了初步成效。

关键词：人-机交互视线追踪普尔钦斑

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人机互信的知识自动化与混合增强智能：复杂系统认知管控机制及其应用 Research Article

王飞跃1,郭剑波2,卜广全3,张俊4

《信息与电子工程前沿（英文）》 2022年第23卷第8期页码 1142-1157 doi: 10.1631/FITEE.2100418

摘要：本文旨在阐述复杂系统认知、管理和控制中人机互信的混合增强智能和知识自动化机制与应用。本文从复杂系统研究的发展历程出发，通过对复杂系统的特性、人工智能科技、人机混合增强智能科技及其在复杂系统管控中的必要性阐述，分析了人类智能、机器智能在复杂系统管控中的优势与局限性，并提出“人机互信知识自动化”的概念。以电力系统大电网调控为背景，阐述了未来人机混合智能在大电网调度中可能的技术路径和应用基础，并以潮流校正控制为例，说明人机知识自动化任务流程的完成过程。通过本文内容的阐述，希望对基于人机混合增强智能的复杂系统管理和控制的理论方法提供一种新的机制和应用路径，并对社会典型复杂系统管控的数字化、智能化建设起到积极作用。

关键词：复杂系统；人机知识自动化；平行系统；大电网调度；人工智能；智联网

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人工智能走向2.0

潘云鹤

《工程（英文）》 2016年第2卷第4期页码 409-413 doi: 10.1016/J.ENG.2016.04.018

摘要：

随着互联网的普及、传感网的渗透、大数据的涌现、信息社区的崛起，以及数据和信息在人类社会、物理空间和信息空间之间的交叉融合与相互作用，当今人工智能(AI) 发展所处信息环境和数据基础已经发生了深刻变化，人工智能的目标和理念正面临重要调整，人工智能的科学基础和实现载体也面临新的突破，人工智能正进入一个新的阶段。这个源于传统而又与之不同的人工智能新阶段被称为人工智能2.0(AI 2.0)。本文从人工智能60 年的发展历史出发，通过分析促成人工智能2.0形成的外部环境与目标的转变，分析技术萌芽，提出了人工智能2.0 的核心理念，并结合中国发展的社会需求与信息环境特色，给出了发展人工智能2.0 的建议。

关键词：人工智能2.0 大数据群体智能跨媒体人机混合智能无人智能系统