OpenAI的研究人员在一个模拟的捉迷藏游戏中展示了涌现的工具使用能力，代理在没有明确指令的情况下开发了复杂的策略。通过多代理竞争，代理学会了与物体互动和导航环境，展示了自我监督的自动课程。这项研究表明，多代理协同适应可能在未来带来高度复杂的行为，利用与OpenAI Five等先前OpenAI项目类似的训练基础设施。 AI
排序理由 该集群描述了OpenAI的一篇研究论文，详细介绍了在模拟环境中涌现的工具使用能力，属于研究类别。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
We’ve observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek. Through training in our new simulated hide-and-seek environment, agents build a series of six distinct strategies and counterstrategies, some of which we did not kn…
<p>It seems like everyone is uses the term “agent” differently these days. In this episode, Chris and Daniel dig into the details of tool calling and its connection to agents. They help clarify how LLMs can “talk to” and “interact with” other systems like databases, APIs, web app…