Abstract: Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behavior due to the imprecise physical processes associated with their formation. Modeling the behavior of such materials in geotechnical engineering applications is complex and sometimes beyond the ability of most traditional forms of physically-based engineering methods. In recent years, the application of artificial intelligence (AI) in a wide range of geotechnical engineering has grown rapidly. AI can be very useful in solving problems where deterministic solutions are not available or are excessively expensive in terms of computational cost but for which there are significant observations and data available. Due to the nature of materials, geotechnical engineering deals with more uncertainties than other fields of civil and mechanical engineering. There is also much monitoring and site investigation data in geotechnical engineering which needs to be taken advantage of by using data analytic methods. Therefore, AI can be a suitable and effective alternative route to solving geotechnical engineering problems and significant developments have been made in recent years as much attention has been given to the area.

Key words: Artificial intelligence; Geotechnical engineering; Big data

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