Intuitive interactive flow:cognitive loop for complex human-machine collaborative task allocation
The rapid development of artificial intelligence technology has led to a fundamental transformation from Human-Machine Interaction(HMI)to Human-Machine Collaboration(HMC).The HMC's core objective is to fully leverage the comple-mentary advantages of human wisdom and machine intelligence to maximize the efficiency of task execution within the framework of human-machine collaboration.The essential differences in intelligent performance between humans and machines were explored from the perspectives of philosophy and neuroscience.Two typical modes of human behavior in human-machine interaction were clearly defined:skill-based intuitive behavior and knowledge-based intellectual behavior.The concept of"interaction flow"was brought forward combined human intuition with machine humanoid intelligence.A cognitive loop model was constructed for com-plex human-machine task allocation.The EEG(Electroencephalograph)activities of experts and novices during specific task exe-cution were measured by neurophysiological experiments.The differences in their behavioral patterns and corresponding neural patterns were compared and summarized,which preliminarily validated the rationality of the constructed model.
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