This study focuses on group intelligence and synchronization phenomena in complex systems by analyzing an enhanced self-directed swarmalator model. In this model, individuals not only move through space and interact with each other but also adjust their phase coupling strength according to their own tendencies, resulting in various self-organizing patterns. Through numerical simulations and theoretical derivations, multiple dynamical states exhibiting radial or layered symmetry have been uncovered, and the system undergoes notable transitions at specific parameter thresholds. During this process, individual diversity, along with “like-attracts-like” or “opposites-attract” strategies, plays a pivotal role in shaping the global spatial configuration and phase evolution, providing potential insights for control strategies and multiscale optimization in novel distributed systems.

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• Coupled oscillators
• Dynamics of networks
• Synchronization