Self-evolving Agents with reflective and memory-augmented abilities
<|reference_start|>Self-evolving Agents with reflective and memory-augmented abilities: 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.<|reference_end|>
@article{liang2024self-evolving,
    title={Self-evolving Agents with reflective and memory-augmented abilities},
    author={Xuechen Liang, Meiling Tao, Yinghui Xia, Tianyu Shi, Jun Wang,
  JingSong Yang},
    journal={arXiv preprint arXiv:2409.00872},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.00872},
    primaryClass={cs.CL}
}