Swarm Architectures

AI Agent Swarms: Multi-Agent Debate & Context Routing

PoC Architecture Design

This Proof of Concept (PoC) explores hierarchical Multi-Agent Swarms, emphasizing the Actor Model and Context Routing for distributed intelligence.

Core Mechanics

1. The Actor Model (Erlang/Akka inspired): Agents are isolated nodes communicating exclusively via asynchronous message passing. There is no shared memory. Each Agent maintains its own KV cache and system prompt.
2. Context Routing: The "Router Agent" classifies the user intent using a fast SLM (e.g., Llama 3 8B) and dispatches the raw prompt + relevant context to specialized worker agents.
3. Multi-Agent Debate: When a complex task requires resolution, two "Debater Agents" generate conflicting proposals, and a "Judge Agent" synthesizes the final output.

Architecture Map

%%{init: {"theme": "default", "flowchart": {"useMaxWidth": true}}}%%
flowchart TD
    subgraph Client ["Client Layer"]
        A["User Request"]
    end
    
    subgraph Router ["Context Routing (Fast SLM)"]
        B["Intent Classification"]
        C["Context Enrichment (RAG)"]
    end
    
    subgraph Swarm ["Autonomous Swarm"]
        D["Specialist A (Code)"]
        E["Specialist B (Research)"]
        F["Debate Arena"]
        G["Judge Synthesizer"]
    end
    
    A -->|"Send Prompt"| B
    B -->|"Lookup DB"| C
    C -->|"Dispatch Task"| D
    C -->|"Dispatch Task"| E
    D -->|"Proposal A"| F
    E -->|"Proposal B"| F
    F -->|"Evaluate"| G
    G -->|"Return Result"| A