For complex dynamical systems in the real-world, we expect to analyze the systems and discover certain general laws behind the diverse phenomena or forecast the future variation of systems states. We further expect to synthesize strategies to control, manage, or guide the systems, based on our knowledge from systems analysis, either qualitative or quantitative.

Social systems are among the most complex systems. It is usually impossible to build analytical models due to the ubiquitous uncertainty, nonlinearity, unobservability, time delay, variation of parameters or topologies in time, and ultra-large-scale. It has been a greatly challenging task to deal with these systems. Cyber-physical-social systems (CPSS) are generalized from cyber-physical systems, integrating parallel systems: a real-world system in physical-social space, and its virtual-world counterpart(s) in cyber space, through man-in-loop information and control flows binding them together. Many of the cyber space images are agent-based, homogeneous, or heterogeneous. For complex objects with social properties, a promising methodology for effectively analyzing and synthesizing is based on the framework of CPSS, with the ideas of artificial societies, computational experiments, and parallel executions jointly employed. Hybrid enhanced intelligence would emerge from a comprehensive integration of knowledge-driven description, data-driven observation, experiment-driven prediction, and practice-driven adaptation.

This Special Issue aims to provide a forum to discuss the recent advances in parallel analysis, control, or intelligence toward various complex systems with sociality. Articles originated from solid theoretical tracks or engineering backgrounds are particularly encouraged. Original research and review articles are both welcome.

Potential topics include but are not limited to the following:

• Social computing
• Multi-agent systems
• Digital twin
• Internet of Things
• Data acquisition for CPSS
• Information fusion for CPSS
• Modelling and cognization for CPSS
• Control and decision for CPSS
• Technical applications of CPSS