Integrating Socialized Learning into Edge Intelligence: Enhancing Collaboration, Adaptability, and Security in Networked Systems

Socialized learning (SL) is a promising solution that can address the challenges faced by edge intelligence (EI) systems, such as communication costs, resource allocation, and privacy concerns. By incorporating social principles and behaviors, SL can enhance the collaborative capacity and collective intelligence of agents within the EI system, leading to improved adaptability, optimized communication and networking processes, and enhanced security.