Intuitive interaction flow: A dual-loop human‒machine collaboration task allocation model and an experimental study

This study investigates the issue of task allocation in human‒machine collaboration (HMC). By integrating philosophical insights and cognitive science, it clearly defines two typical modes of human states in human‒machine interactions: skill-based intuitive states and knowledge-based intellectual states. Building on this, the concept of “intuitive interaction flow” is innovatively introduced by combining human intuition with machine humanoid intelligence, leading to the construction of a dual-loop HMC task allocation model. Through comparative experiments measuring electroencephalogram (EEG) and electromyogram (EMG) activities, distinct physiological patterns associated with these states are identified, providing a preliminary foundation for future adaptive HMC frameworks. This work offers a pathway for developing intelligent HMC systems that effectively integrate human intuition and machine intelligence.