Abstract
With the development of artificial intelligence technology, intelligent machines are increasingly equipped with human-like abilities such as autonomous decision-making, reasoning, active interaction, and situation awareness. Intelligent machines can act as peers to humans and collaborate with humans to complete decision tasks. The ability to collaborate with humans has become an indicator of the intelligence level of a machine, and determines the scope and depth of its applications. Human-machine collaborative decision-making has attracted attentions from multi-disciplines in recent years, and the diverse origins of its developments make the mechanism of collaborative decision-making ambiguous. A thorough combing of the evolution of human-machine collaboration based on cognitive intelligence is of great importance for understanding the nature of human-machine collaboration at the decision layer and guiding future studies. This article makes a retrospect on the evolution of human-machine collaborative decision-making based on cognition intelligence. It summarizes current research in three categories: the human-machine collaborative system implementation, the human-machine intelligence integrative mechanism and the human-machine interaction in collaborative decision-making process. It reveals the roadmap of the evolution of intelligent machines toward human-machine integration intelligence. Based on the roadmap, prospects for future research of human-machine collaborative decision-making are discussed.
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This work is supported by the National Natural Science Foundation of China (72188101) and the National Social Science Foundation of China (20&ZD125).
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Nengying Chen performed the literature search, analysis, and wrote the manuscript under the supervision of Minglun Ren, who had the idea for the article. All authors read and approved the final manuscript.
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Ren, M., Chen, N. & Qiu, H. Human-machine Collaborative Decision-making: An Evolutionary Roadmap Based on Cognitive Intelligence. Int J of Soc Robotics 15, 1101–1114 (2023). https://doi.org/10.1007/s12369-023-01020-1
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DOI: https://doi.org/10.1007/s12369-023-01020-1