Neuro-symbolic approaches in artificial intelligence
National Science Review, 9 (6):
nwac035 (March 2022)DOI: 10.1093/nsr/nwac035
Abstract
Neuro-symbolic artificial intelligence refers to a field of research and applications that combines machine learning methods based on artificial neural networks, such as deep learning, with symbolic approaches to computing and artificial intelligence (AI), as can be found for example in the AI subfield of knowledge representation and reasoning. Neuro-symbolic AI has a long history; however, it remained a rather niche topic until recently, when landmark advances in machine learning—prompted by deep learning—caused a significant rise in interest and research activity in combining neural and symbolic methods. In this overview, we provide a rough guide to key research directions, and literature pointers for anybody interested in learning more about the field.