多代理协调模式：五种方法及其适用时机

In an earlier post, we explored when multi-agent systems provide value and when a single agent is the better choice. This post is for teams that have made that call and now need to decide which coordination pattern fits their problem.

在之前的帖子中，我们探讨了 multi-agent systems 何时提供价值，以及何时 single agent 是更好的选择。本帖适用于已经做出该决定的团队，现在需要决定哪种 coordination pattern 适合他们的问题。

We've seen teams choose patterns based on what sounds sophisticated rather than what fits the problem at hand. We recommend starting with the simplest pattern that could work, watching where it struggles, and evolving from there. This post examines the mechanics and limitations of five patterns:

我们见过团队根据听起来复杂的东西选择模式，而不是适合手头问题的东西。我们建议从可能有效的简单模式开始，观察它在哪里挣扎，然后从中演化。本文考察了五种模式的机制和局限性：

Generator-verifier, for quality-critical output with explicit evaluation criteria
Generator-verifier，适用于具有明确评估标准质量关键输出
Orchestrator-subagent, for clear task decomposition with bounded subtasks
Orchestrator-subagent，用于清晰的任务分解，具有边界明确的子任务
Agent teams, for parallel, independent, long-running subtasks
Agent teams，用于并行、独立、长时间运行的子任务
Message bus, for event-driven pipelines with a growing agent ecosystem
Message bus，适用于具有不断增长的 agent 生态系统的 event-driven pipelines
Shared-state, for collaborative work where agents build on each other's findings
Shared-state，用于代理基于彼此发现进行协作工作的场景

Pattern 1: Generator-verifier

This is the simplest multi-agent pattern and among the most deployed. We introduced it as the verification subagent pattern in our previous post, and here we use the broader generator-verifier framing because the generator need not be an orchestrator.

这是最简单的多智能体模式，也是部署最多的之一。我们在上一篇文章中将其介绍为验证子智能体模式，这里我们使用更广泛的生成器-验证器框架，因为生成器不必是 orchestrator。

How it works

工作原理

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A generator receives a task and produces an initial output, which it passes to a verifier for evaluation. The verifier checks whether the output meets the required criteria and either accepts it as complete or rejects it with feedback. If rejected, that feedback is routed back to the generator, which uses it to pro...