提醒大模型规划研究回归严谨，借鉴传统规划经验避免重复踩坑
Make Planning Research Rigorous Again!
- 将自动化规划领域的工具数据融入大模型规划系统设计
- 指出当前研究普遍重复历史已知的错误模式
- 适合关注大模型规划可靠性的研究者参考
自诞生六十余年来，规划领域在理论与实践上为解决全新规划问题提供了重要贡献，这得益于严格的系统设计与评估方法。我们主张，当前大语言模型（LLM）驱动的规划研究也应遵循同样严谨标准。关键路径是正确引入自动化规划社区的洞见、工具和数据，以指导LLM规划器的设计与评估。该领域的经验不仅是历史遗产，更可加速新型规划系统的研发。鉴于近期大量工作反复出现规划社区早已识别并克服的陷阱，避免这些旧错将极大推动LLM规划及整个规划领域的发展。
原文摘要 · Abstract (English)
In over sixty years since its inception, the field of planning has made significant contributions to both the theory and practice of building planning software that can solve a never-before-seen planning problem. This was done through established practices of rigorous design and evaluation of planning systems. It is our position that this rigor should be applied to the current trend of work on planning with large language models. One way to do so is by correctly incorporating the insights, tools, and data from the automated planning community into the design and evaluation of LLM-based planners. The experience and expertise of the planning community are not just important from a historical perspective; the lessons learned could play a crucial role in accelerating the development of LLM-based planners. This position is particularly important in light of the abundance of recent works that replicate and propagate the same pitfalls that the planning community has encountered and learned from. We believe that avoiding such known pitfalls will contribute greatly to the progress in building LLM-based planners and to planning in general.
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