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Review on the Research and Practice of Hybrid-augmented Intelligence in Power Systems
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作者 Shixiong Fan Jianbo Guo +2 位作者 Yijun Zeng Dongqi Li Shicong Ma 《CSEE Journal of Power and Energy Systems》 2025年第6期2535-2552,共18页
Hybrid-augmented intelligence(HAI)technology is a viable and significant growth paradigm for the implementation of artificial intelligence(AI)in power systems.It is used to address the challenges of ensuring the secur... Hybrid-augmented intelligence(HAI)technology is a viable and significant growth paradigm for the implementation of artificial intelligence(AI)in power systems.It is used to address the challenges of ensuring the secure and trustworthy application of AI models,caused by uncertainty,openness,and the vulnerability of the power grid.First,this paper explores the concept and connotations of human-machine hybrid-augmented intelligence(HHI)technology and summarizes its application development in the fields of autonomous driving,robotics,medical treatment,and the military.A paradigm for the application of HAI in power systems is then proposed,in combination with the construction of HAI systems and human-machine collaboration(HMC)modes for power systems.This study systematically reviews the advancements and core technologies of HAI in power systems,focusing on four aspects:human-machine-intelligence modeling,machine-enhanced human,human-enhanced machine,and human-machine interaction(HMI).Additionally,a practical case of HAI for power grid regulation and control is given.Finally,this paper analyzes the key technical challenges faced by HAI in power systems.It provides an outlook aimed at promoting and enriching the development of basic theories and key technologies for the safe and trustworthy application of HAI in power systems. 展开更多
关键词 Artificial intelligence human-machine collaboration human-machine hybrid-augmented intelligence hybrid-augmented intelligence power systems
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Hybrid-augmented intelligence: collaboration and cognition 被引量:83
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作者 Nan-ning ZHENG Zi-yi LIU +6 位作者 Peng-ju REN Yong-qiang MA Shi-tao CHEN Si-yu YU Jian-ru XUE Ba-dong CHEN Fei-yue WANG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2017年第2期153-179,共27页
The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems t... The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models: one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given. 展开更多
关键词 Human-machine collaboration hybrid-augmented intelligence Cognitive computing Intuitivereasoning Causal model Cognitive mapping Visual scene understanding Self-driving cars
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Heading toward Artificial Intelligence 2.0 被引量:144
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作者 Yunhe Pan 《Engineering》 SCIE EI 2016年第4期409-413,共5页
With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society... With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the develoDment of Al 2.0 are given. 展开更多
关键词 Artificial intelligence 2.0 Big data Crowd intelligence CROSS-MEDIA Human-machine hybrid-augmented intelligence Autonomous-intelligent system
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Human-AI Cooperation in Education: Human in Loop and Teaching as leadership 被引量:3
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作者 Feng Chen 《教育技术与创新》 2022年第1期14-25,共12页
Using the differences and complementarities between human intelligence and artificial intelligence(AI),a hybrid-augmented intelligence,that is both stronger than human intelligence and AI,is created through Human-AI C... Using the differences and complementarities between human intelligence and artificial intelligence(AI),a hybrid-augmented intelligence,that is both stronger than human intelligence and AI,is created through Human-AI Cooperation(HAC)for teaching and learning.Human-AI Cooperation is infiltrating into all links of education,and recent research has focused a lot on the impact of teaching,learning,management,and evaluation with Human-AI Cooperation.However,AI still has its limits of intelligence,and cannot cooperate as humans.Thus,it is critical to study the obstacles of Human-AI Cooperation in education,as AI plays a role as a partner,not a tool.This study discussed for the first time how teachers and AI cooperate based on Multiple Intelligences of AI proposed by Andrzej Cichocki and puts forward a new Human-AI Cooperation teaching mode:human in the loop and teaching as leadership.It is proposed that humans in the loop and teaching as leadership can solve the problem that AI cannot cope with complex and dynamic teaching tasks in open situations,as well as the limits of intelligence for AI. 展开更多
关键词 Human-AI Cooperation EDUCATION Human in Loop Teaching as leadership Multiagents Multiple intelligences Emotional intelligence Social intelligence Creative Intelligence Innovative intelligence Ethical and moral intelligence hybrid-augmented intelligence
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