将AI规划与自然语言处理相结合：显性知识与隐性知识的融合
Integrating AI Planning with Natural Language Processing: A Combination of Explicit and Tacit Knowledge
AI总结：
本文首次系统综述AI规划与自然语言处理的深层联系，提出二者通过基于规划的文本理解、NLP、可解释性、人机交互及应用五个方面相互促进，融合显性与隐性知识以改善人机通信。
摘要：
自然语言处理（NLP）旨在研究智能体与人类之间的交互，处理和分析大量的自然语言数据。大规模语言模型在当前自然语言处理中发挥着重要作用。然而，语言模型的发展也带来了可解释性和复杂性方面的挑战。一种方法是将逻辑关系和规则引入自然语言处理模型，例如利用自动规划。自动规划（AI planning）专注于构建符号化领域模型，并基于领域模型合成从初始状态过渡到目标状态的规划方案。近年来，这两个领域涌现出大量相关工作，它们分别具备生成显性知识（如动作模型的前提条件和效果）和从隐性知识（如神经模型）中学习的能力。将AI规划与自然语言处理有效结合，能够改善人类与智能体之间的通信。本文概述了AI规划与自然语言处理之间的共性和关系，论证了二者可以通过五个方面相互产生有效影响：（1）基于规划的文本理解，（2）基于规划的自然语言处理，（3）基于规划的可解释性，（4）基于文本的人机交互，以及（5）应用。我们还探讨了AI规划与自然语言处理之间一些潜在的未来问题。据我们所知，本综述是首篇论述AI规划与自然语言处理之间深层联系的工作。
英文摘要：
Natural language processing (NLP) aims at investigating the interactions between agents and humans, processing and analyzing large amounts of natural language data. Large-scale language models play an important role in current natural language processing. However, the challenges of explainability and complexity come along with the developments of language models. One way is to introduce logical relations and rules into natural language processing models, such as making use of Automated Planning. Automated planning (AI planning) focuses on building symbolic domain models and synthesizing plans to transit initial states to goals based on domain models. Recently, there have been plenty of works related to these two fields, which have the abilities to generate explicit knowledge, e.g., preconditions and effects of action models, and learn from tacit knowledge, e.g., neural models, respectively. Integrating AI planning and natural language processing effectively improves the communication between human and intelligent agents. This paper outlines the commons and relations between AI planning and natural language processing, argues that each of them can effectively impact on the other one by five areas: (1) planning-based text understanding, (2) planning-based natural language processing, (3) planning-based explainability, (4) text-based human-robot interaction, and (5) applications. We also explore some potential future issues between AI planning and natural language processing. To the best of our knowledge, this survey is the first work that addresses the deep connections between AI planning and Natural language processing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
