发表机构
Amazon AGI（亚马逊通用人工智能）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
介绍多智能体自动研究系统词汇表，规定智能体、操作等多方面内容，将结构设计问题转化为可测试选择，使评估器成系统组件，还区分生成性品味和评估性品味，并在自动研究系统上实例化说明其涵盖多种不同结构设计。
AI 中文摘要
我们为基于一个或多个智能体构建的自动研究系统引入了一个词汇表，以使它们的设计选择更易于描述和比较。该词汇表规定了：智能体是谁；系统中有哪些可用操作；谁可以调用这些操作；智能体如何通信；运行期间及不同运行之间可见的信息有哪些；下一个动作如何选择；运行如何开始；输出如何评估。轨迹记录从输入任务到返回工件的一次运行。由于智能体、操作和初始化可能是随机的，对同一任务的重复运行会在轨迹上产生分布而非单一行为。我们的词汇表将结构设计问题转化为可测试的选择，还使评估器成为系统的一个组件。生成性品味是系统在观察到任何分数之前提出新轨迹的速率，评估性品味是代理分数与其应匹配的质量之间的差距。我们在最近的自动研究系统上实例化了该词汇表，以说明它涵盖了结构差异很大的设计。
英文摘要
We introduce a vocabulary for automated research systems built from one or more agents to make their design choices easier to describe and compare. The vocabulary specifies 1) who the agents are, 2) what operations are available in the system, 3) who may invoke them, 4) how agents communicate, 5) what information is visible within and across runs, 6) how the next action is chosen, 7) how a run begins, and 8) how outputs are evaluated. A trajectory records one run from the input task to the returned artifact. Because agents, operations, and initialization may be stochastic, repeated runs on the same task induce a distribution over trajectories rather than a single behavior. Our vocabulary turns structural design questions, such as when agents should communicate, gain or lose a capability, or carry information across runs, into testable choices. It also makes the evaluator a component of the system, since reported gains depend on how closely the proxy score matches true quality. That separation also splits the vague complaint that these systems lack taste into two failures with different solutions. Generative taste is the rate at which a system proposes novel trajectories before any score is observed, and evaluative taste is the gap between the proxy score and the quality it should match. We instantiate the vocabulary on recent autoresearch systems to illustrate that it covers designs that differ widely in structure.
Comments22 pages, 4 figures, 3 tables
