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

Donald KENNEDY, Simon P. PHILBIN

Frontiers of Engineering Management 2018, Volume 5, Issue 2,   Pages 182-194 doi: 10.15302/J-FEM-2018085

Abstract: Machine intelligence is increasingly entering roles that were until recently dominated by human intelligenceTherefore, 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 presentedWe offer that the speed at which new human-machine interactions are being encountered by engineeringHuman-machine systems are becoming pervasive yet this research has revealed that current technological

Keywords: human intelligence & machine intelligence     HI-MI     decision-making     artificial intelligence    

Big data and machine learning: A roadmap towards smart plants

Frontiers of Engineering Management   Pages 623-639 doi: 10.1007/s42524-022-0218-0

Abstract: and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligenceand machine learning, cloud computing, and virtual and augmented reality.Exploitation of the information contained in these data requires the use of advanced machine learningand artificial intelligence technologies integrated with more traditional modelling techniques.

Keywords: big data     machine learning     artificial intelligence     smart sensor     cyber–physical system     Industry 4.0    

Heading toward Artificial Intelligence 2.0

Yunhe Pan

Engineering 2016, Volume 2, Issue 4,   Pages 409-413 doi: 10.1016/J.ENG.2016.04.018

Abstract: space, and cyberspace, the information environment related to the current development of artificial intelligence

Keywords: Artificial intelligence 2.0     Big data     Crowd intelligence     Cross-media     Human-machine     hybrid-augmented     intelligence    

Artificial intelligence and statistics Perspective

Bin YU, Karl KUMBIER

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 1,   Pages 6-9 doi: 10.1631/FITEE.1700813

Abstract: Artificial intelligence (AI) is intrinsically data-driven.It calls for the application of statistical concepts through human-machine collaboration during the generationThis paper discusses how such human-machine collaboration can be approached through the statistical concepts

Keywords: Artificial intelligence     Statistics     Human-machine collaboration    

Current applications of artificial intelligence for intraoperative decision support in surgery

Allison J. Navarrete-Welton, Daniel A. Hashimoto

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 369-381 doi: 10.1007/s11684-020-0784-7

Abstract: Research into medical artificial intelligence (AI) has made significant advances in recent years, including

Keywords: artificial intelligence     decision support     clinical decision support systems     intraoperative     deep learning     computer vision     machine learning     surgery    

Automated synthesis of steady-state continuous processes using reinforcement learning

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 288-302 doi: 10.1007/s11705-021-2055-9

Abstract: Automated flowsheet synthesis is an important field in computer-aided process engineering. The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics or prior knowledge of conceptual design. The environment consists of a steady-state flowsheet simulator that contains all physical knowledge. An agent is trained to take discrete actions and sequentially build up flowsheets that solve a given process problem. A novel method named SynGameZero is developed to ensure good exploration schemes in the complex problem. Therein, flowsheet synthesis is modelled as a game of two competing players. The agent plays this game against itself during training and consists of an artificial neural network and a tree search for forward planning. The method is applied successfully to a reaction-distillation process in a quaternary system.

Keywords: automated process synthesis     flowsheet synthesis     artificial intelligence     machine learning     reinforcement    

New directions for artificial intelligence: human, machine, biological, and quantum intelligence Comment

Li WEIGANG,Liriam Michi ENAMOTO,Denise Leyi LI,Geraldo Pereira ROCHA FILHO

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 6,   Pages 984-990 doi: 10.1631/FITEE.2100227

Abstract: Upon analyzing the current state of research in artificial intelligence (AI), we propose to divide AIinto the following basic theory categories: artificial human intelligence (AHI), artificial machineintelligence (AMI), artificial biological intelligence (ABI), and artificial quantum intelligence (AQI;D) within AI, and distinguished by the following classification standards and methods: (1) human-, machine

Keywords: 人工智能;机器学习;一次性学习;一瞥学习;量子计算    

Toward Intelligent Machine Tool Article

Jihong Chen, Pengcheng Hu, Huicheng Zhou, Jianzhong Yang, Jiejun Xie, Yakun Jiang, Zhiqiang Gao, Chenglei Zhang

Engineering 2019, Volume 5, Issue 4,   Pages 679-690 doi: 10.1016/j.eng.2019.07.018

Abstract: development of modern information technology—and particularly of the new generation of artificial intelligence(AI) technology—new opportunities are available for the development of the intelligent machineThree stages of machine tool evolution—from the manually operated machine tool (MOMT) to the IMT—are discussed, including the numerical control machine tool (NCMT), the smart machine tool (SMTof AI technology with advanced manufacturing technology is a feasible and convenient way to advance machine

Keywords: Intelligent manufacturing     Intelligent machine tool     Intelligent numerical controller     New-generation artificialintelligence    

Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats Perspective

Maarten R. Dobbelaere, Pieter P. Plehiers, Ruben Van de Vijver, Christian V. Stevens, Kevin M. Van Geem

Engineering 2021, Volume 7, Issue 9,   Pages 1201-1211 doi: 10.1016/j.eng.2021.03.019

Abstract: Previous efforts a few decades ago to combine artificial intelligence and chemical engineering for modelingMany recent efforts have facilitated the roll-out of machine learning techniques in the research fieldby developing large databases, benchmarks, and representations for chemical applications and new machineMachine learning has significant advantages over traditional modeling techniques, including flexibilityThe greatest threat in artificial intelligence research today is inappropriate use because most chemical

Keywords: Artificial intelligence     Machine learning     Reaction engineering     Process engineering    

Parallel cognition: hybrid intelligence for human-machine interaction and management Research Article

Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1765-1779 doi: 10.1631/FITEE.2100335

Abstract: our parallel cognition learning is effective and feasible for human , and can thus facilitate human-machine

Keywords: Cognitive learning     Artificial intelligence     Behavioral prescription    

Strategies and Principles of Distributed Machine Learning on Big Data Review

Eric P. Xing,Qirong Ho,Pengtao Xie,Dai Wei

Engineering 2016, Volume 2, Issue 2,   Pages 179-195 doi: 10.1016/J.ENG.2016.02.008

Abstract:

The rise of big data has led to new demands for machine learning (ML) systems to learn complex modelsHow can ML computation be bridged with inter-machine communication?

Keywords: Machine learning     Artificial intelligence big data     Big model     Distributed systems     Principles     Theory     Data-parallelism    

Artificial Intelligence in Healthcare: Review and Prediction Case Studies Review

Guoguang Rong, Arnaldo Mendez, Elie Bou Assi, Bo Zhao, Mohamad Sawan

Engineering 2020, Volume 6, Issue 3,   Pages 291-301 doi: 10.1016/j.eng.2019.08.015

Abstract:

Artificial intelligence (AI) has been developing rapidly in recent years in terms of software algorithms

Keywords: Artificial intelligence     Machine learning     Deep learning Neural network     Biomedical research     Healthcare    

Intelligent Petroleum Engineering Perspective

Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen

Engineering 2022, Volume 18, Issue 11,   Pages 27-32 doi: 10.1016/j.eng.2022.06.009

Abstract: phase to oilfield digitization, there has been an increased drive to integrate data-driven modeling and machine

Keywords: Artificial intelligence     Machine learning     Intelligent reservoir engineering     Text mining     Intelligent    

Human-machine augmented intelligence: research and applications Editorial

Jianru XUE, Bin HU, Lingxi LI, Junping ZHANG,jrxue@mail.xjtu.edu.cn,bh@lzu.edu.cn,LL7@iupui.edu,jpzhang@fudan.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1139-1141 doi: 10.1631/FITEE.2250000

Abstract: Current research on artificial intelligence (AI) has been entering a new era, with AI technologies andThe main idea of human-machine augmented intelligence (HAI) is to adopt the role of humans or to embedinterfaces, human-machine coordination and teaming, and advanced perception and smart environments forhuman-machine collaboration.Brain-computer interfaces have become increasingly important among communication channels for human-machine

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms Research Article

Fei-Yue WANG, Jianbo GUO, Guangquan BU, Jun Jason ZHANG,jun.zhang.ee@whu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1142-1157 doi: 10.1631/FITEE.2100418

Abstract: illustrate the concept of mutually trustworthy (HM-KA) as the technical mechanism of hybrid augmented intelligencedescribe the historical development of complex system science and analyze the limitations of human intelligenceand machine intelligence.The need for using human-machine HAI in is then explained in detail.

Keywords: Complex systems     Human-machine knowledge automation     Parallel systems     Bulk power grid dispatch     Artificialintelligence    

Title Author Date Type Operation

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

Donald KENNEDY, Simon P. PHILBIN

Journal Article

Big data and machine learning: A roadmap towards smart plants

Journal Article

Heading toward Artificial Intelligence 2.0

Yunhe Pan

Journal Article

Artificial intelligence and statistics

Bin YU, Karl KUMBIER

Journal Article

Current applications of artificial intelligence for intraoperative decision support in surgery

Allison J. Navarrete-Welton, Daniel A. Hashimoto

Journal Article

Automated synthesis of steady-state continuous processes using reinforcement learning

Journal Article

New directions for artificial intelligence: human, machine, biological, and quantum intelligence

Li WEIGANG,Liriam Michi ENAMOTO,Denise Leyi LI,Geraldo Pereira ROCHA FILHO

Journal Article

Toward Intelligent Machine Tool

Jihong Chen, Pengcheng Hu, Huicheng Zhou, Jianzhong Yang, Jiejun Xie, Yakun Jiang, Zhiqiang Gao, Chenglei Zhang

Journal Article

Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats

Maarten R. Dobbelaere, Pieter P. Plehiers, Ruben Van de Vijver, Christian V. Stevens, Kevin M. Van Geem

Journal Article

Parallel cognition: hybrid intelligence for human-machine interaction and management

Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG

Journal Article

Strategies and Principles of Distributed Machine Learning on Big Data

Eric P. Xing,Qirong Ho,Pengtao Xie,Dai Wei

Journal Article

Artificial Intelligence in Healthcare: Review and Prediction Case Studies

Guoguang Rong, Arnaldo Mendez, Elie Bou Assi, Bo Zhao, Mohamad Sawan

Journal Article

Intelligent Petroleum Engineering

Mohammad Ali Mirza, Mahtab Ghoroori, Zhangxin Chen

Journal Article

Human-machine augmented intelligence: research and applications

Jianru XUE, Bin HU, Lingxi LI, Junping ZHANG,jrxue@mail.xjtu.edu.cn,bh@lzu.edu.cn,LL7@iupui.edu,jpzhang@fudan.edu.cn

Journal Article

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms

Fei-Yue WANG, Jianbo GUO, Guangquan BU, Jun Jason ZHANG,jun.zhang.ee@whu.edu.cn

Journal Article