swarm-orchestration

Multi-agent orchestration coordinates multiple AI agents for complex tasks using patterns like sequential, concurrent, and dynamic routing. You need it when single agents cannot handle distributed workflows or collaborative problem-solving.

To set up sequential multi-agent workflows, apply the sequential architecture pattern to enable linear task progression. This coordinates agents like a researcher, planner, and implementer to execute tasks in a specific order.

Yes, you can run concurrent agents for parallel execution and use the SwarmRouter architecture for dynamic task routing. These orchestration patterns facilitate flexible task management and advanced agent coordination within distributed environments.

The Mixture-of-Agents and GroupChat architectures are the best ways to coordinate collaborative problem solving. These patterns facilitate agent communication and workflow management for complex, distributed AI tasks.

Hierarchical multi-agent orchestration uses pre-defined architectural patterns and communication protocols without requiring external dependencies. You can implement agent coordination and dynamic task routing directly using the provided reference components.