Self-evolving Agents with reflective and memory-augmented abilities

Xuechen Liang; Yangfan He; Yinghui Xia; Xinyuan Song; Jianhui Wang; Meiling Tao; Li Sun; Xinhang Yuan; Jiayi Su; Keqin Li; Jiaqi Chen; Jinsong Yang; Siyuan Chen; Tianyu Shi

arXiv · 2409.00872

Self-evolving Agents with reflective and memory-augmented abilities

Xuechen Liang·Yangfan He·Yinghui Xia·Xinyuan Song·Jianhui Wang·Meiling Tao·Li Sun·Xinhang Yuan·Jiayi Su·Keqin Li·Jiaqi Chen·Jinsong Yang·Siyuan Chen·Tianyu Shi

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Abstract

Large language models (LLMs) have made significant advances in the field of natural language processing, but they still face challenges such as continuous decision-making. In this research, we propose a novel framework by integrating iterative feedback, reflective mechanisms, and a memory optimization mechanism based on the Ebbinghaus forgetting curve, it significantly enhances the agents' capabilities in handling multi-tasking and long-span information.

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Xuechen Liang, Yangfan He, Yinghui Xia, Xinyuan Song, Jianhui Wang, Meiling Tao, Li Sun, Xinhang Yuan, Jiayi Su, Keqin Li, Jiaqi Chen, Jinsong Yang, Siyuan Chen, Tianyu Shi. 2024-09-01. Self-evolving Agents with reflective and memory-augmented abilities. https://arxiv.org/abs/2409.00872

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