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Interactive 3D/Agent Communication Protocols
Communication Pattern
Hub-and-Spoke
All agents communicate through the Orchestrator. No direct agent-to-agent traffic.
Agent Topology
OrchestratorcoordinatorResearchertool useCodercode genReviewerquality
Message Queue
OrchestratorResearchertask delivered
Search for recent ML papers on attention mechanisms
OrchestratorCodertask delivered
Implement a simple transformer block in PyTorch
ResearcherOrchestratorresult delivered
Found 12 papers. Top: FlashAttention-2, MLA, MQA
OrchestratorReviewertask pending
Review the transformer code for correctness
CoderOrchestratorresult pending
transformer.py ready. 87 lines, tested on MNIST.
Pattern
Agents
Orchestrator
Researcher
Coder
Reviewer
pending2
delivered3
failed0
Click a message to highlight the agents and edges involved in that communication.

Agent Communication Protocols - Interactive Visualization

Multi-agent systems rely on structured communication protocols to coordinate work. The three primary patterns are hub-and-spoke (all messages routed through an orchestrator), peer-to-peer (agents communicate directly), and broadcast (one agent sends to all simultaneously). Each pattern has different latency, reliability, and debuggability tradeoffs. Understanding message types - task, result, feedback, error - and their delivery status is essential for building robust agentic pipelines.

  • Hub-and-spoke centralizes control through an orchestrator, simplifying monitoring but creating a bottleneck
  • Peer-to-peer enables faster direct communication but makes message tracing harder
  • Broadcast efficiently distributes updates to all agents but cannot target individual recipients
  • Message status tracking (pending / delivered / failed) is critical for fault-tolerant multi-agent coordination

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.