---
id: 20260517-T0-05
title: "AI智能体设计模式的二维框架：认知功能与执行拓扑"
title_en: "Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Functions and Execution Topology"
url: https://ai.daily.yangsir.net/daily/20260517-T0-05
issue_date: 2026-05-17
publish_date: 2026-05-16T04:00:00.000Z
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2605.13850
---

# AI智能体设计模式的二维框架：认知功能与执行拓扑

本文提出了一个用于大语言模型（LLM）智能体架构的二维设计框架。现有系统多从单一视角描述：如Anthropic、Google和LangChain等行业指南侧重于执行拓扑（即数据流转方式），而认知科学综述则聚焦于认知功能。该框架将两者结合，旨在为智能体设计提供更全面的指导。

## English Version

**Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Functions and Execution Topology**

This article introduces a two-dimensional design framework for Large Language Model (LLM) agent architectures. Current systems are often described from a single perspective. For instance, industry guidelines from Anthropic, Google, and LangChain primarily focus on execution topology, which dictates data flow. Conversely, cognitive science reviews concentrate on underlying cognitive functions. By integrating both dimensions, this framework aims to provide a more comprehensive and holistic approach to AI agent design. It effectively bridges the gap between structural execution and cognitive capabilities, offering developers clearer, actionable guidance to build robust systems.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2605.13850)

**详情页**：https://ai.daily.yangsir.net/daily/20260517-T0-05

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