Social Networks for AI Agents

The deployment of AI agents in collaborative environments requires structured communication and coordination mechanisms. This paper examines the role of social network structures in enabling effective multi-agent systems. We analyze how network topology, communication protocols, and organizational patterns influence agent collaboration. Drawing from recent advances in large language model-based agents and traditional multiagent systems, we identify key challenges and design principles for social networks that support AI agent cooperation. The findings suggest that network structure significantly impacts coordination efficiency, information flow, and task performance in multi-agent systems. We discuss implications for designing scalable agent networks that balance communication costs with collaborative effectiveness.