TravelAgent: An AI Assistant for Personalized Travel Planning
<|reference_start|>TravelAgent: An AI Assistant for Personalized Travel Planning: As global tourism expands and artificial intelligence technology advances, intelligent travel planning services have emerged as a significant research focus. Within dynamic real-world travel scenarios with multi-dimensional constraints, services that support users in automatically creating practical and customized travel itineraries must address three key objectives: Rationality, Comprehensiveness, and Personalization. However, existing systems with rule-based combinations or LLM-based planning methods struggle to fully satisfy these criteria. To overcome the challenges, we introduce TravelAgent, a travel planning system powered by large language models (LLMs) designed to provide reasonable, comprehensive, and personalized travel itineraries grounded in dynamic scenarios. TravelAgent comprises four modules: Tool-usage, Recommendation, Planning, and Memory Module. We evaluate TravelAgent's performance with human and simulated users, demonstrating its overall effectiveness in three criteria and confirming the accuracy of personalized recommendations.<|reference_end|>
@article{chen2024travelagent:,
    title={TravelAgent: An AI Assistant for Personalized Travel Planning},
    author={Aili Chen, Xuyang Ge, Ziquan Fu, Yanghua Xiao, Jiangjie Chen},
    journal={arXiv preprint arXiv:2409.08069},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.08069},
    primaryClass={cs.AI cs.CL}
}