---
id: 20260517-T0-04
title: "PREPING让Agent无需任务数据就能构建记忆，解决冷启动问题"
title_en: "PREPING Builds Agent Memory Without Task Data to Solve Cold Start"
url: https://ai.daily.yangsir.net/daily/20260517-T0-04
issue_date: 2026-05-17
publish_date: 2026-05-16T04:00:00.000Z
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2605.13880
---

# PREPING让Agent无需任务数据就能构建记忆，解决冷启动问题

Agent记忆通常依赖离线演示数据或上线后的交互数据构建，但新Agent进入新环境时面临冷启动空白期。PREPING提出一种无需预先定义任务即可构建Agent记忆的方法，让Agent在部署初期就能具备有用的经验知识。这解决了Agent从零开始适应环境时性能低下的问题，对需要快速部署的自动化场景有直接价值。

## English Version

**PREPING Builds Agent Memory Without Task Data to Solve Cold Start**

Agent memory is typically built from curated demonstrations or post-deployment interactions, leaving a cold-start gap when agents enter new environments. PREPING proposes building agent memory without predefined tasks, enabling agents to acquire useful experiential knowledge from the start. This solves the poor initial performance problem, offering direct value for automation scenarios requiring rapid deployment.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2605.13880)

**详情页**：https://ai.daily.yangsir.net/daily/20260517-T0-04

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