Swarm Orchestration

Multi-agent coordination is managed by orchestrating swarms using topologies like mesh, hierarchical, or adaptive. This dynamically assigns and balances tasks across agents for efficient parallel or pipeline execution in distributed AI systems.

Dynamic topology adaptation in distributed AI systems allows a multi-agent swarm to reconfigure its coordination structure on the fly. It supports load balancing and fault tolerance by adjusting how agents interact during complex task execution.

Yes, running multi-agent swarms requires agentic-flow v3.0.0-alpha.1 or higher and Node.js 18+. These dependencies provide the foundational framework needed to initialize the swarm and spawn individual agents.

To set up a mesh swarm, you initialize it with a specified agent capacity and then spawn distinct agents for coding, testing, and reviewing. This ensures seamless collaboration and efficient delivery for complex software features.

The best way to handle load balancing and fault tolerance in multi-agent workflows is using an orchestration layer that supports dynamic topology adaptation. It continuously redistributes tasks across available agents to prevent bottlenecks.