Self-evolving Agents with reflective and memory-augmented abilities

• URL: http://arxiv.org/abs/2409.00872v1
• Date: Sun, 1 Sep 2024 23:36:34 GMT
• Title: Self-evolving Agents with reflective and memory-augmented abilities
• Authors: Xuechen Liang, Meiling Tao, Yinghui Xia, Tianyu Shi, Jun Wang, JingSong Yang,
• Abstract summary: 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. We propose a novel framework by integrating iterative feedback, reflective mechanisms, and a memory optimization mechanism based on the Ebbinghaus forgetting curve.
• Score: 8.123272461141815
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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