Exploration of Key Variables That Trigger Intelligent Emergent Behavior in ICSoS

Intelligent emergence is a key characteristic that dis-tinguishes Intelligent Complex Systems of Systems (ICSoS) from complex systems, yet it has long lacked in-depth explanation. Focusing on exploring the triggering mechanisms of intelligent emergence in ICSoS, we innovatively propose related conceptual definitions and basic assumptions, concentrating on two key variables “Component Connectivity” and “Component Intelligence Level”. We reveal that within ICSoS, there are key factors similar to targets, which exert a ripple effect on overall system performance. Numerical simulation results show that components in ICSoS with high connectivity exhibit stronger information transmission and collaboration capabilities, enabling them to effectively adapt to and respond to changes in the external environment. In contrast, components with low connectivity face issues such as obstructed information transmission and inefficient collaboration, making it difficult to respond effectively in complex environments in a timely manner. Additionally, a high Component Intelligence Level indicates that components possess greater perception, decision-making, and execution abilities, al-lowing for more effective interaction and collaboration with other components. Conversely, a low Component Intelligence Level may lead to limitations and deficiencies in the ICSoS's ability to cope with complex environments and tasks. Furthermore, the experiments also reveal that a high Component Intelligence Level is typically accompanied by a pursuit of high Component Connectivity, tending to establish more connections with other components to achieve higher levels of information sharing and collaboration.