MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendation
<|reference_start|>MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendation: LLM-based Multi-Agent Systems have potential benefits of complex decision-making tasks management across various domains but their applications in the next Point-of-Interest (POI) recommendation remain underexplored. This paper proposes a novel MAS4POI system designed to enhance next POI recommendations through multi-agent interactions. MAS4POI supports Large Language Models (LLMs) specializing in distinct agents such as DataAgent, Manager, Analyst, and Navigator with each contributes to a collaborative process of generating the next POI recommendations.The system is examined by integrating six distinct LLMs and evaluated by two real-world datasets for recommendation accuracy improvement in real-world scenarios. Our code is available at https://github.com/yuqian2003/MAS4POI.<|reference_end|>
@article{wu2024mas4poi:,
    title={MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendation},
    author={Yuqian Wu, Yuhong Peng, Jiapeng Yu, and Raymond S. T. Lee},
    journal={arXiv preprint arXiv:2409.13700},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.13700},
    primaryClass={cs.IR cs.AI cs.SI}
}