让AI理解自然语言任务并自动规划执行，提升办公效率。
GenPlanX. Generation of Plans and Execution
- 结合大模型与经典规划引擎，解析自然语言任务
- 在办公场景中成功生成并执行任务计划
- 适合需要人机协作的自动化办公场景
传统人工智能规划技术能为复杂任务生成动作序列，但无法理解以自然语言描述的规划任务。大型语言模型（LLMs）在人机交互中展现出解读人类意图的优异能力。本文提出GenPlanX，将LLM与经典AI规划引擎结合，并配备执行与监控框架，实现基于自然语言的任务描述与自动规划执行。我们在办公相关任务中验证了GenPlanX的有效性，展示了其通过无缝人机协作优化工作流程、提升生产力的潜力。
原文摘要 · Abstract (English)
Classical AI Planning techniques generate sequences of actions for complex tasks. However, they lack the ability to understand planning tasks when provided using natural language. The advent of Large Language Models (LLMs) has introduced novel capabilities in human-computer interaction. In the context of planning tasks, LLMs have shown to be particularly good in interpreting human intents among other uses. This paper introduces GenPlanX that integrates LLMs for natural language-based description of planning tasks, with a classical AI planning engine, alongside an execution and monitoring framework. We demonstrate the efficacy of GenPlanX in assisting users with office-related tasks, highlighting its potential to streamline workflows and enhance productivity through seamless human-AI collaboration.
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