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Emergence mechanisms of group consensus in social networks

《工程管理前沿（英文）》 doi: 10.1007/s42524-023-0277-x

摘要： Reaching consensus within larger social network groups has emerged as a pivotal concern in the digital age of connectivity. This article redefines group consensus as the emergence of collective intelligence resulting from self-organizing actions and interactions of individuals within a social network group. In our exploration of extant research on group consensus, we illuminate two frequently underestimated, yet noteworthy facets: Dynamism and emergence. In contrast to the conventional perspective of consensus as a mere outcome, we perceive it as an ongoing, dynamic process. This process encompasses self-organized communication and interaction among group members, collectively guiding the group towards cognitive convergence and viewpoint integration. Consequently, it is imperative to redirect our focus from the outcomes of group interactions to an examination of the relationships and processes underpinning consensus formation, thus elucidating the mechanisms responsible for the generation of group consensus. The amalgamation of cognitive contexts and accurate simplification of real-world scenarios for simulation and experimental analysis offers a pragmatic operational approach. This study contributes novel theoretical underpinnings and quantitative insights for establishing and sustaining group consensus within the realm of engineering management practices. Concurrently, it holds substantial importance for advancing the broader research landscape pertaining to social consensus.

关键词： group consensus social network collective intelligence

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群智进化理论及其在智能机器人中的应用

戚骁亚,刘创,富宸,甘中学

《中国工程科学》 2018年第20卷第4期页码 101-111 doi: 10.15302/J-SSCAE-2018.04.017

摘要：

群体智能（CI）已经在过去的几十年里被广泛研究。最知名的CI算法就是蚁群算法（ACO），它被用来通过CI涌现解决复杂的路径搜索问题。最近，DeepMind发布的AlphaZero程序，通过从零开始的自我对弈强化学习，在围棋、国际象棋、将棋上都取得了超越人类的成绩。通过在五子棋上试验并实现AlphaZero系列程序，以及对蒙特卡洛树搜索（MCTS）和ACO两种算法的分析和比较，AlphaZero的成功原因被揭示，它不仅是因为深度神经网络和强化学习，而且是因为MCTS算法，该算法实质上是一种CI涌现算法。在上述研究基础上，本文提出了一个CI进化理论，并将其作为走向人工通用智能（AGI）的通用框架。该算法融合了深度学习、强化学习和CI算法的优势，使得单个智能体能够通过CI涌现进行高效且低成本的进化。此CI进化理论在智能机器人中有天然的应用。一个云端平台被开发出来帮助智能机器人进化其智能模型。作为这个概念的验证，一个焊接机器人的焊接参数优化智能模型已经在云端平台上实现。

关键词：群体智能涌现进化正反馈蚁群算法蒙特卡洛树搜索分布式人工智能云端平台智能机器人

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群体智能中的追逃围捕问题综述 Review

穆祯鑫1,2,潘杰1,周子烨1,喻俊志1,曹璐2

《信息与电子工程前沿（英文）》 2023年第24卷第8期页码 1093-1116 doi: 10.1631/FITEE.2200590

摘要：对于人工系统中涌现出的复杂功能，理解自然界中生物群体行为的内在机制至关重要。本文对生物集群中的一个关键问题—追逃围捕问题进行了全面的综述。首先，从博弈论、控制论与人工智能、生物启发3个不同视角对追逃围捕问题进行了回顾。然后，概述了生物系统和人工系统中追逃围捕问题研究进展，其中捕食者的追捕行为和猎物的逃避行为被概括为捕食者—猎物行为。之后，分别从强追捕者组vs.弱逃避者组、弱追捕者组vs.强逃避者组、相同能力组3个角度分析追逃围捕问题在人工系统中的应用。最后，讨论了未来追逃围捕问题面临的挑战和发展展望。本文为多智能体系统和多机器人系统在不确定动态场景下完成复杂狩猎任务的设计提供了新的见解。

关键词：群体行为；追逃问题；人工系统；生物模型；群集运动

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INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS

《农业科学与工程前沿（英文）》 2023年第10卷第4期页码 648-653 doi: 10.15302/J-FASE-2023505

摘要：

Enhancement of farming management relies heavily on enhancing farmer knowledge. In the past, both the direct learning approach and the personnel extension system for improving fertilization practices of smallholders has proven insufficiently effective. Therefore, this article proposes an interactive knowledge learning approach using artificial intelligence as a promising alternative. The system consists of two parts. The first is a dialog interface that accepts information from farmers about their current farming practices. The second part is an intelligent decision system, which categorizes the information provided by farmers in two categories. The first consists of on-farm constraints, such as fertilizer resources, split application times and seasons. The second comprises knowledge-based practices by farmers, such as nutrient in- and output balance, ratios of different nutrients and the ratios of each split nutrient amount to the total nutrient input. The interactive knowledge learning approach aims to identify and rectify incorrect practices in the knowledge-based category while considering the farmer’s available finance, labor, and fertilizer resources. Investigations show that the interactive knowledge learning approach can make a strong contribution to prevention of the overuse of nitrogen and phosphorus fertilizers, and mitigating agricultural non-point source pollution.

关键词： artificial intelligence extension system non-point source pollution control smallholders fertilization

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Artificial intelligence in gastroenterology: where are we heading?

Joseph JY Sung, Nicholas CH Poon

《医学前沿（英文）》 2020年第14卷第4期页码 511-517 doi: 10.1007/s11684-020-0742-4

摘要： Artificial intelligence (AI) is coming to medicine in a big wave. From making diagnosis in various medical conditions, following the latest advancements in scientific literature, suggesting appropriate therapies, to predicting prognosis and outcome of diseases and conditions, AI is offering unprecedented possibilities to improve care for patients. Gastroenterology is a field that AI can make a significant impact. This is partly because the diagnosis of gastrointestinal conditions relies a lot on image-based investigations and procedures (endoscopy and radiology). AI-assisted image analysis can make accurate assessment and provide more information than conventional analysis. AI integration of genomic, epigenetic, and metagenomic data may offer new classifications of gastrointestinal cancers and suggest optimal personalized treatments. In managing relapsing and remitting diseases such as inflammatory bowel disease, irritable bowel syndrome, and peptic ulcer bleeding, convoluted neural network may formulate models to predict disease outcome, enhancing treatment efficacy. AI and surgical robots can also assist surgeons in conducting gastrointestinal operations. While the advancement and new opportunities are exciting, the responsibility and liability issues of AI-assisted diagnosis and management need much deliberations.

关键词： artificial intelligence endoscopy robotics gastrointestinal diseases

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The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social

Yujia Peng,Jiaheng Han,Zhenliang Zhang,Lifeng Fan,Tengyu Liu,Siyuan Qi,Xue Feng,Yuxi Ma,Yizhou Wang,Song-Chun Zhu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.006

摘要： The release of the generative pre-trained transformer (GPT) series has brought artificial general intelligence (AGI) to the forefront of the artificial intelligence (AI) field once again. However, the questions of how to define and evaluate AGI remain unclear. This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions (DEPSI). More specifically, we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system. The Tong test describes a value- and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI, allowing for infinite task generation. We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized, quantitative, and objective benchmarks and evaluation of AGI.

关键词： Artificial general intelligence Artificial intelligence benchmark Artificial intelligence evaluation Embodied artificial intelligence Value alignment Turing test Causality

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智能源于人、拓于工——人工智能发展的一点思考

蒋昌俊,王俊丽

《中国工程科学》 2018年第20卷第6期页码 93-100 doi: 10.15302/J-SSCAE-2018.06.015

摘要：

人工智能（AI）旨在模拟人脑中信息存储和处理机制等智能行为，使机器具有一定程度的智能水平。随着互联网、大数据、云计算和深度学习等新一代信息技术的飞速发展，目前AI领域的研究和应用已经取得重要进展。本文将深入分析与AI密切相关的计算机科学、控制科学、类脑智能、人脑智能等学科或领域之间的交融与历史演进；指出神经科学、脑科学与认知科学中有关脑的结构与功能机制的研究成果，为构建智能计算模型提供了重要的启发，并从逻辑模型及系统、神经元及网络模型、视觉神经分层机制等方面，分别阐述智能的驱动与发展；最后从互联网的计算理论、AI的演算和计算的融合、类脑智能的模型和机理、AI对神经科学的推动作用、反馈计算的算法设计与控制系统的能级五个方面，对AI的发展趋势进行了展望。

关键词：人工智能人脑智能类脑智能智能发展学科演进

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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

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HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK

《农业科学与工程前沿（英文）》 2022年第9卷第1期页码 150-154 doi: 10.15302/J-FASE-2021419

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Artificial intelligence in radiotherapy: a technological review

Ke Sheng

《医学前沿（英文）》 2020年第14卷第4期页码 431-449 doi: 10.1007/s11684-020-0761-1

摘要： Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have occurred in the past 30 years. These advances, such as three-dimensional image guidance, intensity modulation, and robotics, created challenges and opportunities for the next breakthrough, in which artificial intelligence (AI) will possibly play important roles. AI will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others, particularly those with increased complexity because of technological advances. The improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the society. Furthermore, AI may provide new functionalities that facilitate satisfactory RT. The functionalities include superior images for real-time intervention and adaptive and personalized RT. AI may effectively synthesize and analyze big data for such purposes. This review describes the RT workflow and identifies areas, including imaging, treatment planning, quality assurance, and outcome prediction, that benefit from AI. This review primarily focuses on deep-learning techniques, although conventional machine-learning techniques are also mentioned.

关键词： artificial intelligence radiation therapy medical imaging treatment planning quality assurance outcome prediction

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The linkage mechanism between urban intelligence and low carbon innovation

Ming LIN

《工程管理前沿（英文）》 2019年第6卷第4期页码 584-586 doi: 10.1007/s42524-019-0076-6

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支持科学决策和咨询的技术——思维系统工程

戴汝为

《中国工程科学》 2005年第7卷第1期页码 17-20

摘要：

思维科学及思维系统工程的研究，可为科学决策和咨询提供理论基础与技术支持。建立和启动一个开放的思维巨系统——思维系统工程，是一项崭新的工程技术。论述了社会思维与群体智慧；综合集成研讨厅的框架结构及技术构件；基于internet的综合集成研讨厅实例。

关键词：科学决策思维科学社会思维群体智慧

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Application of artificial intelligence in surgery

Xiao-Yun Zhou, Yao Guo, Mali Shen, Guang-Zhong Yang

《医学前沿（英文）》 2020年第14卷第4期页码 417-430 doi: 10.1007/s11684-020-0770-0

摘要： Artificial intelligence (AI) is gradually changing the practice of surgery with technological advancements in imaging, navigation, and robotic intervention. In this article, we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots. We conclude this review by summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery.

关键词： artificial intelligence surgical autonomy medical robotics deep learning

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Determination of shear strength of steel fiber RC beams: application of data-intelligence models

Abeer A. AL-MUSAWI

《结构与土木工程前沿（英文）》 2019年第13卷第3期页码 667-673 doi: 10.1007/s11709-018-0504-4

摘要： Accurate prediction of shear strength of structural engineering components can yield a magnificent information modeling and predesign process. This paper aims to determine the shear strength of steel fiber reinforced concrete beams using the application of data-intelligence models namely hybrid artificial neural network integrated with particle swarm optimization. For the considered data-intelligence models, the input matrix attribute is one of the central element in attaining accurate predictive model. Hence, various input attributes are constructed to model the shear strength “as a targeted variable”. The modeling is initiated using historical published researches steel fiber reinforced concrete beams information. Seven variables are used as input attribute combination including reinforcement ratio ( ), concrete compressive strength ( ), fiber factor ( ), volume percentage of fiber ( ), fiber length to diameter ratio ( ) effective depth ( ), and shear span-to-strength ratio ( ), while the shear strength ( ) is the output of the matrix. The best network structure obtained using the network having ten nodes and one hidden layer. The final results obtained indicated that the hybrid predictive model of ANN-PSO can be used efficiently in the prediction of the shear strength of fiber reinforced concrete beams. In more representable details, the hybrid model attained the values of root mean square error and correlation coefficient 0.567 and 0.82, respectively.

关键词： hybrid intelligence model shear strength prediction steel fiber reinforced concrete