Sistemas multi-agente
Definición
Los sistemas multi-agente involucran múltiples agentes de IA que interactúan para resolver tareas: collaboration (divide work, share state), debate (argue and refine answers), or specialized roles (planner, executor, critic).
Extienden single agents when one model or one loop is insufficient: por ej. one agent for RAG recuperación, another for generation, another for critique. Subagents are a hierarchical form where a root agent delegates to children; here we focus on flat or peer-to-peer multi-agent patterns.
Cómo funciona
El usuario envía una tarea a un orquestador (que puede ser un LLM o un flujo de trabajo fijo). El orquestador asigna trabajo al Agente1, Agente2, etc.tc., each with its own role, tools, and optionally model. Agents may share a common state, pass messages, or be invoked in sequence/parallel. Their outputs are aggregated (por ej. combined, voted, or summarized) and returned to the user. Design choices include role assignment, communication protocol, and conflict resolution. MAS are useful when you want modularity (each agent has a clear responsibility), specialization (different models or tools per role), reusability (same agent in different workflows), and structured control flow.
Casos de uso
Los sistemas multi-agente ayudan cuando un solo agente no es suficiente: se necesitan roles distintos, debate o pipelines modulares.
- Orchestrating planner, executor, and critic agents for complex tasks
- Debate or review flows where multiple agents refine an answer
- Specialized pipelines (por ej. one agent for recuperación, one for generation)
Documentación externa
- From Prototypes to Agents with ADK – Google Codelabs — ADK supports composing multiple agents into a multi-agent system
- LangChain – Multi-agent — Multi-agent orchestration patterns