Swarm Orchestration

Multi-agent swarms coordinate complex distributed AI tasks by applying mesh, hierarchical, and adaptive topologies for parallel task execution. This approach enables shared state management and coordination across multiple agents simultaneously.

Mesh topologies connect all agents directly for decentralized coordination, hierarchical topologies organize agents in parent-child layers for structured control, and adaptive topologies dynamically adjust agent connections based on task flow and load requirements.

Fault tolerance and load balancing are applied during swarm orchestration to redistribute tasks during agent failures and balance execution loads across the swarm. This maintains reliable parallel processing and shared state across distributed agents.

Swarm orchestration requires agentic-flow v3.0.0-alpha.1+ and Node.js 18+. These dependencies provide the foundational runtime and framework support needed to initialize multi-agent topologies and execute parallel distributed tasks.

Yes, hooks integration supports pre-task and post-task coordination within multi-agent swarms. This allows you to execute custom logic before distributing tasks to agents and after parallel execution completes, enabling advanced workflow control.

You should use multi-agent swarm orchestration when complex distributed AI tasks require parallel execution, fault tolerance, or load balancing that exceeds a single agent's capacity. It is ideal for scaling shared state and coordination across mesh or hierarchical topologies.