Swarm Orchestration

Swarm orchestration coordinates distributed tasks by managing multiple agents across mesh, hierarchical, or adaptive topologies. It provides automatic task distribution, load balancing, and fault tolerance for complex, long-running workflows.

To set up a mesh topology for parallel task orchestration, you define the network structure, spawn the required agents, and initiate parallel task distribution. The system automatically balances the load and coordinates memory across the swarm.

Yes, multi-agent orchestration supports fault tolerance and session or state sharing. It maintains synchronization across long-running tasks using pre-task and post-task hooks to ensure resilient workflow execution even if individual agents fail.

Use hierarchical topologies for structured, tiered task delegation and adaptive topologies for dynamic, self-adjusting workloads. Both provide automatic task distribution and load balancing, but adaptive structures flexibly reconfigure based on real-time agent states.

Yes, you can integrate synchronization hooks across multi-agent swarm workflows. The orchestration system supports pre-task and post-task hooks to synchronize states, coordinate memory, and manage complex dependencies across varying agent types.

Adaptive topology load balancing requires strict memory coordination and hook-based integration to function correctly. Without proper topology setup and state sharing, complex distributed-systems workflows may fail to synchronize or recover from agent faults.