There has been an increasing demand for underground construction due to urbanization and limited land in metropolitan cities in the recent years. However, the behavior of underground structures in soils and rocks is often not completely understood. The emergence of Artificial Intelligence (AI) techniques is envisaged to have a huge potential in addressing geotechnical problems that involve complex soil-structure interaction. This paper thus aims at reviewing the applications of AI techniques in studying underground soil-structure interaction, which focuses on aspects such as characterization of soils and rocks, pile foundations, deep excavations and tunneling. An overview of different AI techniques is provided and a list of key AI applications in underground works that have been published in the last ten years is also compiled to study the recent trend of machine learning techniques in underground construction. The capabilities and limitations of these techniques are discussed throughout the paper, to help readers understand various techniques that are suitable for different underground geotechnical applications. Lastly, some of the challenges that may be faced when applying the techniques are identified, and recent development of AI in geotechnical engineering is discussed in which possible countermeasures to overcome these limitations are highlighted.

近年来，由于城市化和大城市城市土地有限，对地下建筑的需求不断增长。但是，人们对土壤和岩石中地下结构的行为往往不甚了解。设想人工智能（AI）技术的出现在解决涉及复杂土壤与结构相互作用的岩土工程问题方面具有巨大潜力。因此，本文旨在综述AI技术在研究地下土壤与结构的相互作用中的应用，该研究着重于诸如土石的表征，桩基，深基坑和隧道等方面。提供了各种AI技术的概述，并汇总了最近十年发布的地下工程中的关键AI应用列表，以研究地下建筑中机器学习技术的最新趋势。整篇文章都讨论了这些技术的功能和局限性，以帮助读者理解适用于不同地下岩土工程应用的各种技术。最后，确定了应用该技术时可能面临的一些挑战，并讨论了岩土工程中AI的最新发展，其中着重指出了克服这些局限性的可能对策。帮助读者了解适用于不同地下岩土应用的各种技术。最后，确定了应用该技术时可能面临的一些挑战，并讨论了岩土工程中AI的最新发展，其中着重指出了克服这些局限性的可能对策。帮助读者了解适用于不同地下岩土应用的各种技术。最后，确定了应用该技术时可能面临的一些挑战，并讨论了岩土工程中AI的最新发展，其中着重指出了克服这些局限性的可能对策。