multi-agent-patterns

Multi-agent system coordination patterns include supervisor/orchestrator, peer-to-peer/swarm, and hierarchical structures. These patterns dictate how agents interact, delegate tasks, and manage dependencies during parallel execution.

Consensus mechanisms in multi-agent coordination work by managing weighted voting, debate protocols, and failure handling among agents. This ensures agents reach agreement on decisions and maintain system reliability during complex task execution.

You can implement a hierarchical multi-agent pattern by structuring agents in a top-down architecture where supervisors delegate tasks to subordinate agents. This approach provides clear chains of command and efficient task distribution for complex workflows.

The best way to coordinate a research team using multiple agents is to assign specialized roles like web search, document retrieval, data analysis, verification, and report generation. Use a supervisor pattern to orchestrate these agents for efficient parallel execution.