Agent Orchestration

Agent orchestration focuses on coordinating multiple AI agents to achieve complex tasks exceeding the capabilities of individual agents. Current research emphasizes efficient methods for automating this coordination, including leveraging large language models for process model generation and refinement, and exploring decentralized architectures for managing AI across diverse networks, such as in 6G deployments. This field is significant for improving the efficiency and scalability of AI systems, impacting diverse applications from software engineering and process modeling to the development of next-generation communication networks. Furthermore, research is actively investigating optimal user interaction paradigms for multi-agent systems, balancing user control with automated orchestration.