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Memp: Exploring Agent Procedural Memory

Runnan Fang, Yuan Liang, Xiaobin Wang, Jialong Wu, Shuofei Qiao, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang

2025-08-11

Memp: Exploring Agent Procedural Memory

Summary

This paper talks about Memp, a system that gives AI agents a special procedural memory to remember and learn from their past experiences in a more organized way.

What's the problem?

The problem is that AI agents often have trouble recalling useful details from past actions to help them perform better on new tasks, which makes them less efficient and less accurate.

What's the solution?

The solution was to design Memp, a memory system where agents can save past experiences as detailed instructions and higher-level concepts, so they can quickly use this stored knowledge to improve their future performance.

Why it matters?

This matters because having better memory helps AI agents learn faster and work smarter, making them more effective in complex tasks and more practical for real-world applications.

Abstract

Agents equipped with a learnable, updatable procedural memory system, Memp, achieve improved performance and efficiency across tasks by distilling past experiences into detailed instructions and higher-level abstractions.