通过ReAct架构连接在一起的。在ReAct提出之前，Acting和Reasoning一直是分开进行的。然而，ReAct的提出使得...
其中reasoning作为推理模块,帮助模型归纳,跟踪和更新动作规划,acting和环境交互收集更多信息(reasoning traces help the model induce, track, and update action plans as well as handle exceptions, while actions allow it to interface with and gather additional information from external sources such as knowledge ...
对于reasoning数据集,benchmark数据有响应变量 思维链: observation的概念是什么? 在概念上理解为环境条件,但是实现时发现是作为LLM的语言输出。 论文的观点:结合推理和行动可以得到更优的效果 分论点: 1.推理reasoning对于行动acting的指导作用(在推理任务上ReAct优于Act) 2.reasoning对于more informed acting的作用?(不...
ReAct: Prompt-based paradigm=Reasoning + Acting 过程:ReAct要求模型以交替地产生 口头推理路径(Verbel Reasoning Traces)和动作(Action),并允许模型动态执行推理过程,维护和调整行动规划(推理 → 行动),还可以与外部环境进行交互(e.g,. wiki),将获得的额外知识用于推理(行动 → 推理)。
设计理念:ReAct方法旨在结合大型语言模型的推理(reasoning)和行动(acting)能力,以解决复杂的语言理解和决策制定任务。它通过生成推理痕迹和任务特定行动,并在执行任务时进行动态推理和从外部环境中获取信息。 工作流程:ReAct方法的工作流程包括以下几个步骤: 模型在执行任务时接收观察结果,并根据这些观察结果生成行动。 行动...
This dissertation investigates aspects of the design of an embodied cognitive agent that interleaves reasoning, acting, and interacting with other agents while maintaining a record of what has happened and is happening in its environment. Among other things, such knowledge of its own history allows ...
邀请直播讲解 While large language models (LLMs) have demonstrated impressive performance on a range of decision-making tasks, they rely on simple acting processes and fall short of broad deployment as autonomous agents. We introduce LATS (Language Agent Tree Search), a general framework that synerg...
2. willing to listen to argument; acting with good sense. You will find him very reasonable.sensato, juicioso 3. fair; correct; which one should or could accept. Is $10 a reasonable price for this book?razonable 4. satisfactory; as much as one might expect or want. There was a reaso...
2022年的论文,引用数超过1000。目前Agent设计的一个重要来源。用几个图可以把文章要点串一遍。 做法很简单,就是在强化学习的Agent(Action + Observation)的基础上,加上推理过程。可以直观地看一下它和其他方法的区别: 在知识密集型推理(KNOWLEDGE-INTENSIVE REASONING TASKS)任务中,ReAct表现接近COT,远优于Standard,最...
本文研究开展于 2022 年,当时 GPT3 已经发布了一段时间,研究人员注意到 LLM 在 CoT 技巧加持下展现出良好的自回归推理能力(称之为仅推理reasoning-only范式);同时,一些用预训练模型作为 agent 的初步研究也验证了 LLM 在各种互动环境中进行规划和行动的能力(仅行动acting-only范式)。但是,当时具有良好推理能力的标...